PRPS2表达特点及其与乳腺癌预后关系的生物信息学分析

doi:10.13481/j.1671-587X.20210521

Abstract

Abstract: Objective

To investigate the expressions of phosphoribosyl pyrophosphate synthetases 2 （PRPS2） in different subtypes of breast cancer and its relationship with the prognosis of breast cancer.

Methods

The transcription levels of PRPS2 in the pan-breast cancer and normal breast tissues were investigated using GEPIA database. Furthermore， UALCAN database was used to analyze the expressions of PRPS2 in the breast cancer and normal breast tissues on the basis of age， menopause status， different subtypes， histologic subtypes， pathological stages， and nodal metastasis status. miRTarBase database was used to predict the miRNAs binding with 3' un-translated region （3'UTR） of PRPS2. Kaplan-Meier plotter database was used to evaluate the relationships between the miRNAs binding with PRPS2 andPRPS23'UTR and the prognosis of breast cancer.

Results

Compared with normal breast tissue，the expression levels of PRPS2 mRNA in different subtypes of breast cancer tissue was significantly increased（P<0.05）.The high expression of PRPS2 mRNA documented the poor prognosis of breast cancer. Compared with normal breast tissue，the expression levels of hsa-miR-215-5p and hsa-miR-26b-5p， the miRNAs binding with 3'UTR of PRPS2，in the different subtypes of breast cancer tissue were significantly reduced（P<0.05）；moreover， the low expression levels of hsa-miR-215 and hsa-miR-26b reflected the poor prognosis of breast cancer.

Conclusion

PRPS2 is of specific expression characteristics of pan-breast cancer， suggesting that the axis of miR-PRPS2-prognosis of breast cancer may exist.

Key words: phosphoribosyl pyrophosphate synthetases 2, bioinformatics, breast neoplasms, prognosis, overall survival

CLC Number:

Yang YU,Sainan LIU,Yunkai LIU,Yong LI,Yichun QIAO,Yi CHENG. Bioinformatic analysis on expression characteristics of PRPS2 and its relationship with prognosis of breast cancer[J].Journal of Jilin University(Medicine Edition), 2021, 47(5): 1229-1236.

Figures/Tables 6

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References 23

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Correlated gene	Cytoband	Spearman’s correlation	P value	q value
CCSAP	1q42.13	0.402	1.46E-38	2.95E-34
POLA1	Xp22.11-p21.3	0.396	1.87E-37	1.88E-33
NKRF	Xq24	0.389	4.04E-36	2.47E-32
TIPRL	1q24.2	0.389	4.90E-36	2.47E-32
FANCB	Xp22.2	0.381	1.54E-34	6.23E-31
UBA2	19q13.11	0.374	3.17E-33	1.07E-29
UCHL5	1q31.2	0.368	3.49E-32	1.01E-28
MMS22L	6q16.1	0.357	2.92E-30	6.54E-27
GMPS	3q25.31	0.356	4.22E-30	8.35E-27
LIN9	1q42.12	0.356	4.93E-30	8.35E-27
PIGA	Xp22.2	0.356	4.97E-30	8.35E-27
HPRT1	Xq26.2-q26.3	0.352	2.44E-29	3.68E-26
C4ORF46	4q32.1	0.352	2.55E-29	3.68E-26
SPIN4	Xq11.1	0.351	3.27E-29	4.40E-26
FAM72A	1q32.1	0.350	4.72E-29	5.94E-26
KIF14	1q32.1	0.349	6.16E-29	6.90E-26
AHCTF1	1q44	0.348	8.64E-29	9.18E-26
PPP1CB	2p23.2	0.347	1.30E-28	1.32E-25
CACYBP	1q25.1	0.347	1.66E-28	1.60E-25
HCCS	Xp22.2	0.346	2.37E-28	2.18E-25
DEPDC1	1p31.3	0.344	3.94E-28	3.31E-25
ZNF124	1q44	0.344	4.96E-28	4.01E-25
ACTL6A	3q26.33	0.344	5.49E-28	4.26E-25
TTK	6q14.1	0.343	6.57E-28	4.90E-25
DKC1	Xq28	0.342	8.88E-28	6.39E-25

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Bioinformatic analysis on expression characteristics of PRPS2 and its relationship with prognosis of breast cancer

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