Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma

Abstract

BackgroundClear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney cancer, and its incidence and mortality are not optimistic. It is well known that tumor-related protein markers play an important role in cancer detection, prognosis prediction, or treatment selection, such as carcinoembryonic antigen (CEA), programmed cell death 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4), so a comprehensive analysis was performed in this study to explore the prognostic value of protein expression in patients with ccRCC.Materials and MethodsProtein expression data were obtained from The Cancer Proteome Atlas (TCPA), and clinical information were downloaded from The Cancer Genome Atlas (TCGA). We selected 445 patients with complete information and then separated them into a training set and testing set. We performed univariate, least absolute shrinkage and selection operator (LASSO) Cox analyses to find prognosis-related proteins (PRPs) and constructed a protein signature. Then, we used stratified analysis to fully verify the prognostic significance of the prognostic-related protein signature score (PRPscore). Besides, we also explored the differences in immunotherapy response and immune cell infiltration level in high and low score groups. The consensus clustering analysis was also performed to identify potential cancer subgroups.ResultsFrom the training set, a total of 233 PRPs were selected, and a seven-protein signature was constructed, including ACC1, AR, MAPK, PDK1, PEA15, SYK, and BRAF. Based on the PRPscore, patients could be divided into two groups with significantly different overall survival rates. Univariate and multivariate Cox regression analyses proved that this signature was an independent prognostic factor for patients (P < 0.001). Moreover, the signature showed a high ability to distinguish prognostic outcomes among subgroups, and the low score group had a better prognosis (P < 0.001) and better immunotherapy response (P = 0.003) than the high score group.ConclusionWe constructed a novel protein signature with robust predictive power and high clinical value. This will help to guide the disease management and individualized treatment of ccRCC patients.

Integrated bioinformatics analysis of the NEDD4 family reveals a prognostic value of NEDD4L in clear-cell renal cell cancer

“…In order to show the reliability of our risk model, we compared it with other ccRCC risk models, and the results showed that our risk model has better prediction ability (Fig. S5) (Zhang, Qiu & Yang, 2021;Fei, Chen & Xu, 2021;Chu et al, 2021;Xing et al, 2021). Based on the complementary perspective of the corresponding tumor, the model provides a personalized score for individual patients and a valuable new prognostic evaluation method for clinicians.…”

Peer Review #1 of "Integrated bioinformatics analysis of the NEDD4 family reveals a prognostic value of NEDD4L in clear-cell renal cell cancer (v0.1)"

“…The ROC analysis of the TCGA testing dataset showed that the AUC was 0.76 at 1 year, 0.69 at 3 years, and 0.68 at 5 years (Figure 6E), while that of the TCGA entire dataset showed that the AUC was 0.74 at 1 year, 0.71 at 3 years, and 0.74 at 5 years (Figure 6F). As reflected by the AUC values at 1 year, 3 year and 5 years, the signatures developed in our work had relatively better performance in predicting outcome of ccRCC patients (Figure 6F, Supplementary Figure 5) (Zhang et al, 2021;Fei et al, 2021;Chu et al, 2021;Xing et al, 2021b).…”

“…According to the calibration graph, there was a significant consistency between the actual and predicted values of the 1 -, 3-and 5-year OS (figure 8). In order to show the reliability of our risk model, we compared it with other ccRCC risk models, and the results showed that our risk model has better prediction ability (Supplementary Figure 5) (Zhang et al, 2021;Fei et al, 2021;Chu et al, 2021;Xing et al, 2021).…”

Angiogenesis-Related Molecular Subtypes and a Novel Prognostic Signature in Clear Cell Renal Cell Carcinoma Patients

“…There have been several prognostic models reported previously. Chu et al 15 constructed a novel seven protein signature for predicting prognosis. Xing et al utilized glycolysis-related genes to successfully establish and externally verify a novel signature for predicting OS of ccRCC.…”