Dataset Information

Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia

ABSTRACT: There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants with a diagnosis of PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model was able to separate PCa from controls with sensitivity of 0.82 and specificity of 0.95, adding BPH resulted in a statistically significant decline in specificity for prostate cancer to 0.76, with half of BPH cases being misclassified by the model as PCa. A small number of biomarkers differentiating between BPH and prostate cancer were identified, including proteins in MAP Kinase pathways, as well as in lipids containing oleic acid; these may offer a route to greater specificity. These results highlight, however, that whilst there are opportunities for machine learning, these will only be achieved by use of appropriate training sets that include confounding comorbidities, especially when calculating the specificity of a test.

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Prostate Adenocarcinoma

SUBMITTER: Lee Gethings

LAB HEAD: Lee Gethings

PROVIDER: PXD046530 | Pride | 2024-01-26

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	Excel_Prostate_Cancer_1_1_001.raw.zip	Raw
	Excel_Prostate_Cancer_1_1_002.raw.zip	Raw
	Excel_Prostate_Cancer_1_1_003.raw.zip	Raw
	Excel_Prostate_Cancer_1_2_001.raw.zip	Raw
	Excel_Prostate_Cancer_1_2_002.raw.zip	Raw

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Publications

Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia.

Spick Matt M Muazzam Ammara A Pandha Hardev H Michael Agnieszka A Gethings Lee A LA Hughes Christopher J CJ Munjoma Nyasha N Plumb Robert S RS Wilson Ian D ID Whetton Anthony D AD Townsend Paul A PA Geifman Nophar N

Heliyon 20231119 12

There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants diagnosed with PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model ...[more]

PMID: 38076065

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Project description:BACKGROUND: Noninvasive methods for the early identify diagnosis of prostatitis, benign prostatic hyperplasia (BPH) and prostate cancer (PCa) are current clinical challenges.METHODS: The serum metabolites of 20 healthy individuals and patients with prostatitis, BPH, or PCa were identified using untargeted liquid chromatography-mass spectrometry (LC-MS).RESULTS: Organic acid metabolites had good sensitivity and specificity in differentiating prostatitis, BPH, and PCa. In addition, targeted LC-MS was used to verify the organic acid metabolites in the serum of a validation cohort. Three diagnostic models identified patients with PROSTATITIS: phenyllactic acid (area under the curve [AUC]=0.773), pyroglutamic acid (AUC=0.725), and pantothenic acid (AUC=0.721). Three diagnostic models identified BPH: citric acid (AUC=0.859), malic acid (AUC=0.820), and D[1]glucuronic acid (AUC=0.810). Four diagnostic models identified PCa: 3-hydroxy-3-methylglutaric acid (AUC=0.804), citric acid (AUC=0.918), malic acid (AUC=0.862), and phenyllactic acid (AUC=0.713). Two diagnostic models distinguished BPH from PCa: phenyllactic acid (AUC=0.769) and pyroglutamic acid (AUC=0.761). Three diagnostic models distinguished benign BPH from PROSTATITIS: citric acid (AUC=0.842), ethylmalonic acid (AUC=0.814), and hippuric acid (AUC=0.733). Six diagnostic models distinguished BPH from prostatitis: citric acid (AUC=0.926), pyroglutamic acid (AUC=0.864), phenyllactic acid (AUC=0.850), ethylmalonic acid (AUC=0.843), 3-hydroxy- 3-methylglutaric acid (AUC=0.817), and hippuric acid (AUC=0.791). Three diagnostic models distinguished PCa patients with PROSTATITISA < 4.0 ng/mL from those with PSA > 4.0 ng/mL: 5-hydromethyl-2-furoic acid (AUC=0.749), ethylmalonic acid (A UC=0.750), and pyroglutamic acid (AUC=0.929).CONCLUSIONS: These results suggest that serum organic acid metabolites can be used as biomarkers to differentiate prostatitis, BPH, and PCa. Targeted organic acid assay is reported in the current study MTBLS6038.Untargeted assay is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS6039' rel='noopener noreferrer' target='_blank'>MTBLS6039</a>.