Development of prognostic index based on autophagy-related genes analysis in breast cancer

Lin, Qi; Liu, Wei; Yu, Miao; Guo, Zhi; Zheng, Wei; Wang, Jian Wei; Li, An Hua; Han, Feng

doi:10.18632/aging.102687

Cited by 33 publications

(38 citation statements)

References 19 publications

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“…Our ROC analysis showed that the AUC was 0.842 for 3-year OS and 0.808 for 5-year OS, higher than the AUC values reported in previous models (Lin et al, 2020;Xie et al, 2019), thus indicating that our model had better predictive ability.…”

Section: Discussioncontrasting

confidence: 75%

Peer Review #1 of "Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes (v0.1)"

2020

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Section: Discussioncontrasting

confidence: 75%

Peer Review #1 of "Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes (v0.1)"

2020

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“…Recently, numerous studies have focused on certain characteristics, such as autophagy and metabolic reprogramming, to identify gene signatures that are able to predict the mortality risk of cancer (Wan et al, 2019;Lin et al, 2020;Liu et al, 2020). In this study, we identified four RBP-related genes that were able to predict the OS of CRC patients.…”

Section: Discussionmentioning

confidence: 99%

Molecular Characterization and Clinical Relevance of RNA Binding Proteins in Colorectal Cancer

et al. 2020

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Abnormal expression of RNA binding proteins (RBPs) has been reported across various cancers. However, the potential role of RBPs in colorectal cancer (CRC) remains unclear. In this study, we performed a systematic bioinformatics analysis of RBPs in CRC. We downloaded CRC data from The Cancer Genome Atlas (TCGA) database. Our analysis identified 242 differentially expressed RBPs between tumor and normal tissues, including 200 upregulated and 42 downregulated RBPs. Next, we found eight RBPs (RRS1, PABPC1L, TERT, SMAD6, UPF3B, RP9, NOL3, and PTRH1) related to the prognoses of CRC patients. Among these eight prognosis-related RBPs, four RBPs (NOL3, PTRH1, UPF3B, and SMAD6) were selected to construct a prognostic risk score model. Furthermore, our results indicated that the prognostic risk score model accurately predicted the prognosis of CRC patients [area under the receiver operating characteristic curve (AUC)for 3-and 5-year overall survival (OS) and was 0.645 and 0.672, respectively]. Furthermore, we developed a nomogram based on a prognostic risk score model. The nomogram was able to demonstrate the wonderful performance in predicting 3-and 5-year OS. Additionally, we validated the clinical value of four risk genes in the prognostic risk score model and identified that these risk genes were associated with tumorigenesis, lymph node metastasis, distant metastasis, clinical stage, and prognosis. Finally, we used the TIMER and Human Protein Atlas (HPA)database to validate the expression of four risk genes at the transcriptional and translational levels, respectively, and used a clinical cohort to validate the roles of NOL3 and UPF3B in predicting the prognosis of CRC patients. In summary, our study demonstrated that RBPs have an effect on CRC tumor progression and might be potential prognostic biomarkers for CRC patients.

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“…Gu Y et al [26] mentioned that eight AGs, BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1, and VEGFA, were ought to be designated as prognostic markers for autophagy-associated BC. Lin QG et al [27] initially found that 27 ARGs (autophagy-related genes) were evidently associated with overall survival rate of BC. The prognostic-related ARGs signature established by the Cox regression consisted of 12 ARGs with a 5-year survival rate AUC 0.742.…”

Section: Discussionmentioning

confidence: 99%

Five crucial prognostic-related autophagy genes stratified female breast cancer patients aged 40-60 years

Zhang

Liu

et al. 2020

Preprint

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Background: Autophagy is closely related to the progression of breast cancer.The aim of this study is to establish a prognostic-related model comprised of hub autophagy-genes(AGs) to assess patitents prognosis. Simultaneously, the model can guide clinicians to make up individualized strategies and stratify patients aged 40-60 years based on risk level.Methods: The hub AGs were identified through univariate COX regression and LASSO regression. The functions and alterations of these selected AGs were analyzed as well.Moreover,the multivariate COX regression and correlation analysis between hub AGs and clinicopathological parameters were done. Results: Totally,33 prognostic-related AGs were obtained from the univariate COX regression(P<0.05).SERPINA1, HSPA8, HSPB8, MAP1LC3A, and DIRAS3 were identified to constitute the prognostic model by the LASSO regression. The survival curve of patients in high-risk and in low-risk group was statistically significant(P<0.05).The 3-year and 5-year ROC displayed that their AUC value reached 0.762 and 0.825,respectively. Stage and riskscore were independent risk factors relevant about prognosis.RB1CC1, RPS6KB1, and BIRC6 were identified as the most predominant mutant genes. It was found that AGs were mainly involved in regulating the endopeptidases synthesis and played important roles in ErbB signal pathway. SERPIN1, riskscore were closely related to stage(P<0.05); HSPA8, riskscore were closely related to T staging(P<0.05); HSPB8 was closely related to N staging(P<0.05). Conclusions: Our prognostic model had relatively robust predictive ability on prognosis for patients aged 40-60 years.If stage was added into the prognostic model, the predictive ability would be more powerful.

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Development of prognostic index based on autophagy-related genes analysis in breast cancer

Cited by 33 publications

References 19 publications

Peer Review #1 of "Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes (v0.1)"

Peer Review #1 of "Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes (v0.1)"

Molecular Characterization and Clinical Relevance of RNA Binding Proteins in Colorectal Cancer

Five crucial prognostic-related autophagy genes stratified female breast cancer patients aged 40-60 years

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