Overexpressed PAQR4 predicts poor overall survival and construction of a prognostic nomogram based on PAQR family for hepatocellular carcinoma

Caihao Qu; Tengda Ma; Xin YAN; Xiaomei Li; Yumin Li; Caihao Qu; Tengda Ma; Xin YAN; Xiaomei Li; Yumin Li

doi:10.3934/mbe.2022142

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 3: 3069-3090. doi: 10.3934/mbe.2022142

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Research article

Overexpressed PAQR4 predicts poor overall survival and construction of a prognostic nomogram based on PAQR family for hepatocellular carcinoma

1.
Lanzhou University Second Hospital, Lanzhou 730030, China
2.
Key Laboratory of Digestive System Tumors of Gansu Province, Lanzhou 730030, China
† These authors have contributed equally to this work

Received: 15 October 2021 Revised: 12 December 2021 Accepted: 03 January 2022 Published: 19 January 2022

Objective
We aimed to explore the expression and clinical prognostic significance of PAQR4 in hepatocellular carcinoma (HCC).

Methods
We obtained the gene expression matrix and clinical data of HCC from the cancer genome atlas (TCGA) and international cancer genome consortium (ICGC) databases. The prognostic value of PAQR4 in HCC was evaluated using the Kaplan-Meier and Cox regression analyses. PAQR4-related pathways were explored by gene set enrichment analysis (GSEA). A clinical nomogram prognostic model based on the PAQR family was constructed using Cox proportional hazards models.

Results
We found that PAQR4 is overexpressed in HCC from multiple databases; additionally, quantitative real-time polymerase chain reaction (qRT-PCR) validated the upregulation of PAQR4 in HCC. PAQR4 expression was related to age, grade, alpha fetoprotein (AFP), T classification and clinical stage of HCC patients. High PAQR4 expression was associated with poor overall survival and was an independent prognostic factor for HCC patients through Kaplan-Meier analysis and Cox regression analysis, respectively. In addition, GSEA identified that the high PAQR4 expression phenotype was involved in the cell cycle, Notch signaling pathway, mTOR signaling pathway, etc. Finally, three PAQR family genes (PAQR4, PAQR8 and PAQR9) were associated with the prognosis of patients with HCC. A clinical nomogram prediction model was verified in TCGA training and ICGC validation sets, and it exerted dramatic predictive efficiency in this study.

Conclusions
PAQR4 may be regarded as a promising prognostic biomarker and therapeutic target for HCC.
- PAQR4,
- hepatocellular carcinoma,
- TCGA,
- prognosis,
- nomogram
Citation: Caihao Qu, Tengda Ma, Xin YAN, Xiaomei Li, Yumin Li. Overexpressed PAQR4 predicts poor overall survival and construction of a prognostic nomogram based on PAQR family for hepatocellular carcinoma[J]. Mathematical Biosciences and Engineering, 2022, 19(3): 3069-3090. doi: 10.3934/mbe.2022142

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Abstract

Objective

We aimed to explore the expression and clinical prognostic significance of PAQR4 in hepatocellular carcinoma (HCC).

Methods

We obtained the gene expression matrix and clinical data of HCC from the cancer genome atlas (TCGA) and international cancer genome consortium (ICGC) databases. The prognostic value of PAQR4 in HCC was evaluated using the Kaplan-Meier and Cox regression analyses. PAQR4-related pathways were explored by gene set enrichment analysis (GSEA). A clinical nomogram prognostic model based on the PAQR family was constructed using Cox proportional hazards models.

Results

We found that PAQR4 is overexpressed in HCC from multiple databases; additionally, quantitative real-time polymerase chain reaction (qRT-PCR) validated the upregulation of PAQR4 in HCC. PAQR4 expression was related to age, grade, alpha fetoprotein (AFP), T classification and clinical stage of HCC patients. High PAQR4 expression was associated with poor overall survival and was an independent prognostic factor for HCC patients through Kaplan-Meier analysis and Cox regression analysis, respectively. In addition, GSEA identified that the high PAQR4 expression phenotype was involved in the cell cycle, Notch signaling pathway, mTOR signaling pathway, etc. Finally, three PAQR family genes (PAQR4, PAQR8 and PAQR9) were associated with the prognosis of patients with HCC. A clinical nomogram prediction model was verified in TCGA training and ICGC validation sets, and it exerted dramatic predictive efficiency in this study.

Conclusions

PAQR4 may be regarded as a promising prognostic biomarker and therapeutic target for HCC.

References

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