Urinary fatty acid biomarkers for prostate cancer detection.
The lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have e...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0297615&type=printable |
| _version_ | 1797304760788844544 |
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| author | Elizabeth Noriega Landa George E Quaye Xiaogang Su Sabur Badmos Kiana L Holbrook Thomas J Polascik Eric S Adams Sriram Deivasigamani Qin Gao Michael H Annabi Ahsan Habib Wen-Yee Lee |
| author_facet | Elizabeth Noriega Landa George E Quaye Xiaogang Su Sabur Badmos Kiana L Holbrook Thomas J Polascik Eric S Adams Sriram Deivasigamani Qin Gao Michael H Annabi Ahsan Habib Wen-Yee Lee |
| author_sort | Elizabeth Noriega Landa |
| collection | DOAJ |
| description | The lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have examined various potential biomarkers for PCa, and of those fatty acids (FAs) markers have received special attention due to their role in cancer metabolomics. It has been noted that PCa metabolism prefers FAs over glucose substrates for continued rapid proliferation. Hence, we proposed using a urinary FAs based model as a non-invasive alternative for PCa detection. Urine samples collected from 334 biopsy-designated PCa positive and 232 biopsy-designated PCa negative subjects were analyzed for FAs and lipid related compounds by stir bar sorptive extraction coupled with gas chromatography/mass spectrometry (SBSE-GC/MS). The dataset was split into the training (70%) and testing (30%) sets to develop and validate logit models and repeated for 100 runs of random data partitioning. Over the 100 runs, we confirmed the stability of the models and obtained optimal tuning parameters for developing the final FA based model. A PSA model using the values of the patients' PSA test results was constructed with the same cohort for the purpose of comparing the performances of the FA model against PSA test. The FA final model selected 20 FAs and rendered an AUC of 0.71 (95% CI = 0.67-0.75, sensitivity = 0.48, and specificity = 0.83). In comparison, the PSA model performed with an AUC of 0.51 (95% CI = 0.46-0.66, sensitivity = 0.44, and specificity = 0.71). The study supports the potential use of urinary FAs as a stable and non-invasive alternative test for PCa diagnosis. |
| first_indexed | 2024-03-08T00:15:10Z |
| format | Article |
| id | doaj.art-7df10a3e5784499daeb41f0d51511fba |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-03-08T00:15:10Z |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-7df10a3e5784499daeb41f0d51511fba2024-02-17T05:32:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01192e029761510.1371/journal.pone.0297615Urinary fatty acid biomarkers for prostate cancer detection.Elizabeth Noriega LandaGeorge E QuayeXiaogang SuSabur BadmosKiana L HolbrookThomas J PolascikEric S AdamsSriram DeivasigamaniQin GaoMichael H AnnabiAhsan HabibWen-Yee LeeThe lack of accuracy in the current prostate specific antigen (PSA) test for prostate cancer (PCa) screening causes around 60-75% of unnecessary prostate biopsies. Therefore, alternative diagnostic methods that have better accuracy and can prevent over-diagnosis of PCa are needed. Researchers have examined various potential biomarkers for PCa, and of those fatty acids (FAs) markers have received special attention due to their role in cancer metabolomics. It has been noted that PCa metabolism prefers FAs over glucose substrates for continued rapid proliferation. Hence, we proposed using a urinary FAs based model as a non-invasive alternative for PCa detection. Urine samples collected from 334 biopsy-designated PCa positive and 232 biopsy-designated PCa negative subjects were analyzed for FAs and lipid related compounds by stir bar sorptive extraction coupled with gas chromatography/mass spectrometry (SBSE-GC/MS). The dataset was split into the training (70%) and testing (30%) sets to develop and validate logit models and repeated for 100 runs of random data partitioning. Over the 100 runs, we confirmed the stability of the models and obtained optimal tuning parameters for developing the final FA based model. A PSA model using the values of the patients' PSA test results was constructed with the same cohort for the purpose of comparing the performances of the FA model against PSA test. The FA final model selected 20 FAs and rendered an AUC of 0.71 (95% CI = 0.67-0.75, sensitivity = 0.48, and specificity = 0.83). In comparison, the PSA model performed with an AUC of 0.51 (95% CI = 0.46-0.66, sensitivity = 0.44, and specificity = 0.71). The study supports the potential use of urinary FAs as a stable and non-invasive alternative test for PCa diagnosis.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0297615&type=printable |
| spellingShingle | Elizabeth Noriega Landa George E Quaye Xiaogang Su Sabur Badmos Kiana L Holbrook Thomas J Polascik Eric S Adams Sriram Deivasigamani Qin Gao Michael H Annabi Ahsan Habib Wen-Yee Lee Urinary fatty acid biomarkers for prostate cancer detection. PLoS ONE |
| title | Urinary fatty acid biomarkers for prostate cancer detection. |
| title_full | Urinary fatty acid biomarkers for prostate cancer detection. |
| title_fullStr | Urinary fatty acid biomarkers for prostate cancer detection. |
| title_full_unstemmed | Urinary fatty acid biomarkers for prostate cancer detection. |
| title_short | Urinary fatty acid biomarkers for prostate cancer detection. |
| title_sort | urinary fatty acid biomarkers for prostate cancer detection |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0297615&type=printable |
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