A cluster of long non-coding RNAs exhibit diagnostic and prognostic values in renal cell carcinoma

Chen, Gong; Liu, Di; Liang, Huageng; Yang, Hongmei; Chen, Ke; Zhang, Xiaoping

doi:10.18632/aging.102407

Cited by 33 publications

(31 citation statements)

References 84 publications

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“…Globally, RCC accounts for more than 2% of neoplasms in humans worldwide with the incidence and mortality persistently increasing 1 . Recently, gene signatures based on specific characteristic-related to predict prognosis have become a hotspot in cancer research 13 – 15 . In the present study, to the best of our knowledge, we constructed the first novel metabolism-related risk signature with the potential application of predicting the prognosis and progression of ccRCC.…”

Section: Discussionmentioning

confidence: 99%

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Liu

Pan

Xiao

et al. 2020

Sci Rep

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Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan-Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with nonmetabolic pathways. In summary, our study provides novel insight into metabolism-related genes' roles in ccRCC. Clear cell renal cell carcinoma (ccRCC), the most common renal cell carcinoma (RCC) subtype, exhibits global health issues due to its growing incidence, extreme heterogeneity among patients and high mortality. It is estimated that 90% of the ccRCC patients died of tumor-specific recurrence and metastasis 1. Regarding this, considerable research efforts have focused on developing a model to predict the prognosis of ccRCC patients; however, these prognosis tools still require improvements to attain a high degree of accuracy 2-4. Therefore, novel and robust prognostic models are urgently needed in clinical practice. Metabolism is fundamental in maintaining all the biological processes necessary for life 5. Tumors are typified by metabolic abnormalities as proliferating cells rewire their mechanism to sustain growth 6. Notably, the rapidly proliferating cells in malignancies take up abundant glucose and glutamine to generate the proteins, lipids, and nucleic acids to support cell growth 7. RCC is regarded as a metabolic disease with diabetes, obesity, and atherosclerosis considered as the risk factors 8,9. CcRCC is a unique RCC subtypes based on the abnormally accumulated lipid droplets in the cytoplasm with research evidence implicating the lipid accumulation in disease progression 10,11. Nevertheless, the underlying mechanism and the prognostic role of these metabolic genes remain largely unknown. In the present study, we screened the differentially expressed metabolism-related genes and evaluated their clinical value based on the cancer genome atlas (TCGA) kidney renal clear ...

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Section: Discussionmentioning

confidence: 99%

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Liu

Pan

Xiao

et al. 2020

Sci Rep

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“…In addition, IGFL2-AS1 was found to be involved in breast cancer progression. 17 In renal cell carcinoma, Cheng et al 18 identified IGFL2-AS1 as a diagnostic and prognostic marker. However, the functional role of IGFL2-AS1 has not been studied in GC.…”

Section: Introductionmentioning

confidence: 99%

LncRNA IGFL2‐AS1 functions as a ceRNA in regulating ARPP19 through competitive binding to miR‐802 in gastric cancer

Liu

et al. 2020

Molecular Carcinogenesis

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Gastric cancer (GC) is one of the most common malignancies of the digestive system worldwide. Multiple long noncoding RNAs (lncRNAs) participate in the regulation of GC development and metastasis. In this study, we aimed to elucidate the expression and function of lncRNA IGFL2‐AS1 in GC. We found that IGFL2‐AS1 was highly expressed in GC tissues and cell lines. Knockdown of IGFL2‐AS1 suppressed GC cell proliferation, migration, and invasion in vitro. Furthermore, we identified that IGFL2‐AS1 exerted its function as a molecular sponge of miR‐802. MiR‐802 was demonstrated to be a tumor suppressor, and overexpression of miR‐802 suppressed GC cell growth, migration, and invasion. Mechanistically, we revealed that the cAMP‐regulated phosphoprotein 19 (ARPP19) was a direct target of miR‐802 and could reverse the inhibitory function of miR‐802. Moreover, our results confirmed that knockdown of IGFL2‐AS1 inhibited GC tumor development in an in vivo GC tumor xenograft model. In summary, our data suggest that the IGFL2‐AS1/miR‐802/ARPP19 axis plays a critical role in the progression and metastasis of GC. Therapies targeting the IGFL2‐AS1/miR‐802/ARPP19 axis can potentially improve GC treatment.

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“…There are more than 1.8 million new cancer cases in the USA alone in 2020, and around 4% of which are estimated to be kidney or renal pelvis tumors (1). Renal cell carcinoma (RCC) is the most common solid tumor of the adult kidney, accounting for 87% of all renal malignant tumors (2). Curative intervention via surgical resection (either partial or radical nephrectomy) has been the primary standard treatment for individuals with clinically localized RCC (3).…”

Section: Introductionmentioning

confidence: 99%

A Meta-Analysis of Glasgow Prognostic Score and Modified Glasgow Prognostic Score as Biomarkers for Predicting Survival Outcome in Renal Cell Carcinoma

et al. 2020

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Purpose: Accumulative studies suggest the Glasgow prognostic score (GPS) and modified Glasgow prognostic score (mGPS) to be potential biomarkers; however, their prognostic value remains debatable. Our meta-analysis focused on assessing the accurate prognostic value of GPS and mGPS in patients with renal cell carcinoma (RCC) in addition to their effectiveness. Methods: To investigate the relationship between mGPS/GPS and prognostic value in patients with RCC, we performed a comprehensive retrieval of relevant articles from databases such as PubMed, Embase, Web of Science, and Medline up to February 1, 2020. STATA 15.0 software was used to obtain pooled hazard ratios (HRs) and their 95% confidence intervals for survival outcome, including overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS), and cancer-specific survival (CSS). A formal meta-analysis of these outcomes was performed. Results: In total, 2,691 patients with RCC were enrolled from 15 cohort studies. Higher GPS/mGPS (GPS/mGPS of 2) indicated poorer OS, CSS, PFS, and RFS in patients with RCC. Similarly, medium GPS/mGPS (GPS/mGPS of 1) also had a significant association with poorer OS, CSS, PFS, and RFS but superior than higher GPS/mGPS in these patients. Conclusion: GPS and mGPS are effective biomarkers for predicting prognosis in patients with RCC, and higher GPS and mGPS are closely related to inferior survival outcomes. More randomized controlled trials are needed to investigate the promising value of GPS/mGPS in the future.

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A cluster of long non-coding RNAs exhibit diagnostic and prognostic values in renal cell carcinoma

Cited by 33 publications

References 84 publications

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

LncRNA IGFL2‐AS1 functions as a ceRNA in regulating ARPP19 through competitive binding to miR‐802 in gastric cancer

A Meta-Analysis of Glasgow Prognostic Score and Modified Glasgow Prognostic Score as Biomarkers for Predicting Survival Outcome in Renal Cell Carcinoma

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