Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Abstract

BackgroundTransforming growth factor (TGF)-β signaling is strongly related to the development and progression of tumor. We aimed to construct a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical prognosis and immunotherapy responses of patients with clear cell renal cell carcinoma (ccRCC).MethodsThe gene expression profiles and corresponding clinical information of ccRCC were collected from the TCGA and the ArrayExpress (E-MTAB-1980) databases. LASSO, univariate and multivariate Cox regression analyses were conducted to construct a prognostic signature in the TCGA cohort. The E-MTAB-1980 cohort were used for validation. Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) were conducted to assess effectiveness and reliability of the signature. The differences in gene enrichments, immune cell infiltration, and expression of immune checkpoints in ccRCC patients showing different risks were investigated.ResultsWe constructed a seven gene (PML, CDKN2B, COL1A2, CHRDL1, HPGD, CGN and TGFBR3) signature, which divided the ccRCC patients into high risk group and low risk group. The K-M analysis indicated that patients in the high risk group had a significantly shorter overall survival (OS) time than that in the low risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p = 0.012). The AUC of the signature reached 0.77 at 1 year, 0.7 at 3 years, and 0.71 at 5 years in the TCGA, respectively, and reached 0.69 at 1 year, 0.72 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Further analyses confirmed the risk score as an independent prognostic factor for ccRCC (p < 0.001). The results of ssGSEA that immune cell infiltration degree and the scores of immune-related functions were significantly increased in the high risk group. The CIBERSORT analysis indicated that the abundance of immune cell were significantly different between two risk groups. Furthermore, The risk score was positively related to the expression of PD-1, CTLA4 and LAG3.These results indicated that patients in the high risk group benefit more from immunotherapy.ConclusionWe constructed a novel TGF-β signaling-related genes signature that could serve as an promising independent factor for predicting clinical prognosis and immunotherapy responses in ccRCC patients.

PML restrains p53 activity and cellular senescence in clear cell renal cell carcinoma

“…It was recently reported that PML is overexpressed in ccRCC compared to normal kidneys and belongs to a high-risk gene signature associated with worse outcome (Wu et al, 2023 ; Luo et al, 2023 ; Wang et al, 2023 ; Li et al, 2019 ). To determine if the PML protein is overexpressed cell-autonomously within ccRCC cells, we compared PML expression in ccRCC cell lines (Caki-1, RCC4, A49786-O and the patient-derived xenograft cell line UTSW-XP258, hereafter referred to as XP258) (Elias et al, 2021 ) with breast cancer (MDA-MB-231, MDA-MB-468, MCF7) and glioblastoma (U87) cell lines, as representative of tumor types where PML is reportedly overexpressed (Carracedo et al, 2012 ; Martín-Martín et al, 2016 ; Ponente et al, 2017 ; Amodeo et al, 2017 ; Aldaz et al, 2022 ; Kuwayama et al, 2009 ; Iwanami et al, 2013 ; Tampakaki et al, 2021 ).…”

“…In a study investigating the role of the SCP1 phosphatase, which promotes PML degradation, it was suggested that PML exerts tumor-suppressive functions in ccRCC (Lin et al, 2014 ). However, more recent studies reported that PML is overexpressed in ccRCC and belongs to gene signatures that identify high-risk patients and correlate with worse disease outcome (Wu et al, 2023 ; Luo et al, 2023 ; Wang et al, 2023 ; Li et al, 2019 ), implying oncogenic activities. Beside this correlative evidence however, a rigorous functional assessment of the involvement of PML in this disease is still lacking.…”

TGF-β signaling in health, disease and therapeutics

“…Serum and tissue levels of TGF-β have shown potential as predictors or indicators of the development, [1074][1075][1076][1077] complication, [1078][1079][1080] response, [1081][1082][1083][1084] recurrence, [1085][1086][1087] and outcomes [1088][1089][1090] of various kinds of diseases, meanwhile, bioinformatic tools of TGF-β signaling-related gene expression signatures have also been developed for patient stratification. 863,1091 But so far, TGF-β or related factors as clinical biomarkers still need further development and assessment.…”

PD1/PD-L1 blockade in clear cell renal cell carcinoma: mechanistic insights, clinical efficacy, and future perspectives

“…Another study established an ERV signature based on nine ERV expression patterns, showing that patients in the low-risk group have better survival outcomes with nivolumab treatment [ 147 ]. A signature composed of PML, CDKN2B, COL1A2, CHRDL1, HPGD, CGN, and TGFBR3 indicates that patients in the high-risk group benefit more from immune therapy [ 148 ]. A gene signature based on FOXM1, TOP2A, KIF18B, and NUF2 shows that patients in the low-risk group have a stronger response to anti-PD1 immune therapy, and PBRM1 mutation is associated with the gene signature [ 149 ].…”