A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer

Abstract

Background Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer. Methods Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores. Results TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) – (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823. Conclusions The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients.

UHMK1 Is a Novel Marker for Personalized Prediction of Pancreatic Cancer Prognosis

“…Finally, we combined UHMK1 expression and clinical parameters to establish a novel prognostic nomogram that individually predicts the 1-, 3-, and 5-year overall survival rates of PDAC patients. To illustrate the reliability of our nomogram, we compared our AUC value to a PDAC nomogram that was constructed by Liu et al., 2021 ( 37 ), who reported AUC values of 0.713, 0.753, and 0.823 for 1-, 3-, and 5-year survival, respectively. Liu’s results suggested their constructed nomogram model had the superior predictive power with AUC value more than 0.7.…”

Recognition of Glycometabolism-Associated lncRNAs as Prognosis Markers for Bladder Cancer by an Innovative Prediction Model

“…The expression of another prognosis-related lncRNA AC011468.1 was repressed in Stage Ⅲ–Ⅳ, which is consistent with the report by Zhao et al (2021) . Also, AL354919.2, Z84484.1, PTOV1-AS2, and MAFG-DT were found to be associated with the prognosis of cancer patients in several studies ( Liu et al, 2021 ; Su et al, 2021 ; Wang et al, 2021 ; Zhao et al, 2021 ). Also, especially, AL354919.2 was obviously upregulated in low-grade BC patients.…”

Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis

“…TAC4 [ 5 ], IGSF1 [ 17 ] and SLC39A8 (ZIP8) [ 24 ]. A prognostic role has also been reported for some of these genes, both negative ( ERRFI1 ) [ 25 ], and positive ( SLC44A3 ) [ 29 ]. Additionally, several of the differentially expressed genes are proposed to be potential therapeutic targets, such as FAIM2 in small cell lung carcinoma [ 18 ], ERRFI1 in pancreatic carcinoma [ 25 ], RASA4 in triple-negative breast carcinoma [ 53 ], FKBP10 in gliomas [ 7 , 18 ], metastatic gastric carcinoma [ 16 ] and lung carcinoma [ 38 ], and CACNA2D in prostate carcinoma [ 18 ].…”

“…Furthermore, many of the genes that we found upregulated in PitNETs have been reported as potential therapeutic targets, e.g. FAIM2 [ 18 ], ERRFI1 [ 25 ], RASA4 [ 53 ], FKBP10 [ 7 , 18 ], and CACNA2D [ 18 ]. This is of interest mostly for patients with Cushing disease, NF-PitNETs and patients with aggressive PitNETs, who presently can be offered none or only limited pharmacological therapeutic options.…”