Background: Cervical cancer (CC) is an important cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.
Methods: We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.
Results: Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P<0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression in tumor tissues while SNX10 showed high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency(AUC= 0.738). GSEA showed that the two genes were associated with the chemokine signaling pathway(P<0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p=0.037). Cox regression analysis showed that SNX10 (P=0.007;HR=1.424;95%CI:1.103-1.838) and PTGDS (P=0.003;HR=0.802;95%CI:0.693-0.928) were independent prognostic indicators for OS among CC patients.
Conclusions: PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients..

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On 30 Dec, 2020
On 20 Dec, 2020
Posted 02 Dec, 2020
On 23 Nov, 2020
On 18 Nov, 2020
On 18 Nov, 2020
On 18 Nov, 2020
On 09 Nov, 2020
Received 07 Nov, 2020
Received 24 Oct, 2020
On 14 Oct, 2020
Invitations sent on 13 Oct, 2020
On 13 Oct, 2020
On 28 Sep, 2020
On 27 Sep, 2020
On 27 Sep, 2020
On 20 Aug, 2020
Received 18 Aug, 2020
Received 16 Aug, 2020
On 11 Aug, 2020
On 09 Aug, 2020
Invitations sent on 08 Aug, 2020
On 08 Aug, 2020
On 28 Jul, 2020
On 28 Jul, 2020
On 27 Jul, 2020
On 27 Jul, 2020
On 30 Dec, 2020
On 20 Dec, 2020
Posted 02 Dec, 2020
On 23 Nov, 2020
On 18 Nov, 2020
On 18 Nov, 2020
On 18 Nov, 2020
On 09 Nov, 2020
Received 07 Nov, 2020
Received 24 Oct, 2020
On 14 Oct, 2020
Invitations sent on 13 Oct, 2020
On 13 Oct, 2020
On 28 Sep, 2020
On 27 Sep, 2020
On 27 Sep, 2020
On 20 Aug, 2020
Received 18 Aug, 2020
Received 16 Aug, 2020
On 11 Aug, 2020
On 09 Aug, 2020
Invitations sent on 08 Aug, 2020
On 08 Aug, 2020
On 28 Jul, 2020
On 28 Jul, 2020
On 27 Jul, 2020
On 27 Jul, 2020
Background: Cervical cancer (CC) is an important cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.
Methods: We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.
Results: Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P<0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression in tumor tissues while SNX10 showed high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency(AUC= 0.738). GSEA showed that the two genes were associated with the chemokine signaling pathway(P<0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p=0.037). Cox regression analysis showed that SNX10 (P=0.007;HR=1.424;95%CI:1.103-1.838) and PTGDS (P=0.003;HR=0.802;95%CI:0.693-0.928) were independent prognostic indicators for OS among CC patients.
Conclusions: PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients..

Figure 1

Figure 1
Figure 2
Figure 2
Figure 3
Figure 3
Figure 4
Figure 4
Figure 5
Figure 5
Figure 6
Figure 6
Figure 7
Figure 7

Figure 8

Figure 8
This is a list of supplementary files associated with this preprint. Click to download.
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