Abstract
Background Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. Methods The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. Results Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. Conclusion Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.
Highlights
Clear cell renal cell carcinoma accounting for more than 75% of all kidney cancers has increasing incidence and mortality rate in the worldwide [1] and tends to be diagnosed in advanced stage [2]
The transcriptome profiling data including raw counts of lncRNAand mRNA-sequencing data and corresponding clinical information of KIRC patients were obtained from The Cancer Genome Atlas (TCGA) dataset in October 2019, in which the methods of acquisition are in line with the guidelines and policies
The related raw counts of RNA-sequencing data and clinical information were acquired from ICGC (International Cancer Genome Consortium, https://icgc.org/), which is a platform for collaboration of worldwide genomic research across 50 cancer types
Summary
Clear cell renal cell carcinoma (ccRCC) accounting for more than 75% of all kidney cancers has increasing incidence and mortality rate in the worldwide [1] and tends to be diagnosed in advanced stage [2]. The Tumor-Node-Metastasis (TNM) staging system, the widely used measure to estimate ccRCC outcomes, is revealed to be insufficient in its predictive value [3]. This would be probably as the result of the heterogeneity of the tumor itself and the complicacy of the Journal of Immunology Research pathogenesis [4]. AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future
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