Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma

Abstract

The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment.

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

“…Potential biomarkers such as lncRNAs play a significant role in guiding treatment decision making. Compared to single lncRNAs, a model constructed with representative lncRNAs may perform better for ccRCC prognosis evaluation 24 . Compared to existing signatures including several lncRNAs (more than 6) 25 , 26 , our 3-lncRNA model contains the fewer genes and should be easy to apply in the clinic.…”

Advances in the Treatment of Kidney and Upper Urinary Tract Cancers

“…This Special Issue aims to cover novel approaches in renal and urothelial cancers. We collected papers focused on novel approaches to urothelial cancers involving upper urinary tract and renal cancers that undertook original research focused on pre-clinical studies and biomarkers [ 9 , 10 , 11 , 12 ], prognostic models [ 13 , 14 , 15 ], the specific population of metastatic patients [ 16 ], and, finally, two narrative reviews [ 17 , 18 ].…”

“…Li et al [ 15 ] focused on the identification of biomarkers of ccRCC and developed a risk model to assess patient prognosis based on the data from the Cancer Genome Atlas (TCGA). They developed a nomogram to predict the prognosis of ccRCC.…”