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 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 separated 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.

SUBMITTER: Spick M

PROVIDER: S-EPMC10709398 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

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

Similar Datasets

Project description:BackgroundThe association between benign prostatic hyperplasia (BPH) and prostate cancer (PCa) remains controversial, largely due to a detection bias in traditional observational studies.ObjectiveTo assess the association between BPH and PCa using inherited single nucleotide polymorphisms (SNPs).Design setting and participantsThe participants were White men from the population-based UK Biobank (UKB).Outcome measurements and statistical analysisThe association between BPH and PCa was tested for (1) phenotypic correlation using chi-square, (2) genetic correlation (r g) based on genome-wide SNPs using linkage disequilibrium score regression, and (3) cross-disease genetic associations based on known risk-associated SNPs (15 for BPH and 239 for PCa), individually and cumulatively using genetic risk score (GRS).Results and limitationsAmong 214 717 White men in the UKB, 24 623 (11%) and 14 311 (6.7%) had a diagnosis of BPH and PCa, respectively. Diagnoses of these two diseases were significantly correlated (χ2 = 1862.80, p < 0.001). A significant genetic correlation was found (r g = 0.16; 95% confidence interval 0.03-0.28, p = 0.01). In addition, significant cross-disease genetic associations for established risk-associated SNPs were also found. Among the 250 established genome-wide association study-significant SNPs of PCa or BPH, 49 were significantly associated with the risk of the other disease at p < 0.05, significantly more than expected by chance (N = 12, p < 0.001; χ2 test). Furthermore, significant cross-disease GRS associations were also found; GRSBPH was significantly associated with PCa risk (odds ratio [OR] = 1.26 [1.18-1.36], p < 0.001), and GRSPCa was significantly associated with BPH risk (OR = 1.03 [1.02-1.04], p < 0.001). Moreover, GRSBPH was significantly and inversely associated with lethal PCa risk in a PCa case-case analysis (OR = 0.58 [0.41-0.81], p = 0.002). Only White men were studied.ConclusionsBPH and PCa share common inherited genetics, which suggests that the phenotypic association of these two diseases in observational studies is not entirely caused by the detection bias.Patient summaryFor the first time, we found that benign prostatic hyperplasia and prostate cancer are genetically related. This finding may have implications in disease etiology and risk stratification.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets