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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: helpers/my_audit_helper.php
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Introduction: Patients with cervical cancer (CC) may experience local recurrence very often after treatment; when only clinical parameters are used, most cases are diagnosed in late stages, which decreases the chance of recovery. Molecular markers can improve the prediction of clinical outcome. Glycolysis is altered in 70% of CCs, so molecular markers of this pathway associated with the aggressiveness of CC can be identified.
Methods: The expression of 14 glycolytic genes was analyzed in 97 CC and 29 healthy cervical tissue (HCT) with microarray; only LDHA and PFKP were validated at the mRNA and protein levels in 36 of those CC samples and in 109 new CC samples, and 31 HCT samples by qRT-PCR, Western blotting, or immunohistochemistry. A replica analysis was performed on 295 CC from The Cancer Genome Atlas (TCGA) database.
Results: The protein expression of LDHA and PFKP was associated with poor overall survival [OS: LDHA HR = 4.0 (95% CI = 1.4-11.1); p = 8.0 × 10 ; PFKP HR = 3.3 (95% CI = 1.1-10.5); p = 4.0 × 10 ] and disease-free survival [DFS: LDHA HR = 4.5 (95% CI = 1.9-10.8); p = 1.0 × 10 ; PFKP HR = 3.2 (95% CI = 1.2-8.2); p = 1.8 × 10 ] independent of FIGO clinical stage, and the results for mRNA expression were similar. The risk of death was greater in patients with overexpression of both biomarkers than in patients with advanced FIGO stage [HR = 8.1 (95% CI = 2.6-26.1; p = 4.3 × 10 ) versus HR = 7 (95% CI 1.6-31.1, p = 1.0 × 10 )] and increased exponentially as the expression of LDHA and PFKP increased.
Conclusions: LDHA and PFKP overexpression at the mRNA and protein levels was associated with poor OS and DFS and increased risk of death in CC patients regardless of FIGO stage. The measurement of these two markers could be very useful for evaluating clinical evolution and the risk of death from CC and could facilitate better treatment decision making.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417302 | PMC |
http://dx.doi.org/10.1002/cam4.6123 | DOI Listing |
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