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. 2023 Jan 29;15(3):821.
doi: 10.3390/cancers15030821.

Circulating Chromosome Conformation Signatures Significantly Enhance PSA Positive Predicting Value and Overall Accuracy for Prostate Cancer Detection

Dmitri Pchejetski  1 , Ewan Hunter  2 , Mehrnoush Dezfouli  2 , Matthew Salter  2 , Ryan Powell  2 , Jayne Green  2 , Tarun Naithani  2 , Christina Koutsothanasi  2 , Heba Alshaker  1 , Jiten Jaipuria  3   4 , Martin J Connor  3 , David Eldred-Evans  3 , Francesca Fiorentino  3   5 , Hashim Ahmed  3 , Alexandre Akoulitchev  2 , Mathias Winkler  3
Affiliations

Circulating Chromosome Conformation Signatures Significantly Enhance PSA Positive Predicting Value and Overall Accuracy for Prostate Cancer Detection

Dmitri Pchejetski et al. Cancers (Basel). .

Abstract

Background: Prostate cancer (PCa) has a high lifetime prevalence (one out of six men), but currently there is no widely accepted screening programme. Widely used prostate specific antigen (PSA) test at cut-off of 3.0 ng/mL does not have sufficient accuracy for detection of any prostate cancer, resulting in numerous unnecessary prostate biopsies in men with benign disease and false reassurance in some men with PCa. We have recently identified circulating chromosome conformation signatures (CCSs, Episwitch® PCa test) allowing PCa detection and risk stratification in line with standards of clinical PCa staging. The purpose of this study was to determine whether combining the Episwitch PCa test with the PSA test will increase its diagnostic accuracy.

Methods: n = 109 whole blood samples of men enrolled in the PROSTAGRAM screening pilot study and n = 38 samples of patients with established PCa diagnosis and cancer-negative controls from Imperial College NHS Trust were used. Samples were tested for PSA, and the presence of CCSs in the loci encoding for of DAPK1, HSD3B2, SRD5A3, MMP1, and miRNA98 associated with high-risk PCa identified in our previous work.

Results: PSA > 3 ng/mL alone showed a low positive predicted value (PPV) of 0.14 and a high negative predicted value (NPV) of 0.93. EpiSwitch alone showed a PPV of 0.91 and a NPV of 0.32. Combining PSA and Episwitch tests has significantly increased the PPV to 0.81 although reducing the NPV to 0.78. Furthermore, integrating PSA, as a continuous variable (rather than a dichotomised 3 ng/mL cut-off), with EpiSwitch in a new multivariant stratification model, Prostate Screening EpiSwitch (PSE) test, has yielded a remarkable combined PPV of 0.92 and NPV of 0.94 when tested on the independent prospective cohort.

Conclusions: Our results demonstrate that combining the standard PSA readout with circulating chromosome conformations (PSE test) allows for significantly enhanced PSA PPV and overall accuracy for PCa detection. The PSE test is accurate, rapid, minimally invasive, and inexpensive, suggesting significant screening diagnostic potential to minimise unnecessary referrals for expensive and invasive MRI and/or biopsy testing. Further extended prospective blinded validation of the new combined signature in a screening cohort with low cancer prevalence would be the recommended step for PSE adoption in PCa screening.

Keywords: PSA; blood test; diagnosis; epigenetics; nucleome; prostate cancer; screening.

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Conflict of interest statement

Ewan Hunter, Matthew Salter, Mehrnoush Dezfouli, Ryan Powel, Jayne Green, Tarun Naithani, Christina Koutsothanasi, and Alexandre Akoulitchev are employees of Oxford BioDynamics. A. Akoulitchev is a company director. Oxford BioDynamics holds patents on the EpiSwitch technology. The remaining authors have no conflict of interest.

Figures

Figure 1
Figure 1
Scheme of chromatin conformation assay and microarray analysis. A three-dimensional structure of chromosomes contains loops with an enhancer and promoter regions, whereas the enhancer increases target gene promoter activity. CC capture assay: DNA is cross-linked using formaldehyde, digested, and ligated with the preference of cross-linked fragments. New sequences are formed where the loops have been. These new sequences are predicted via relevance machine vector algorithm. Specific primers to these sequences are synthesised and placed on the DNA microarray, which detects whether the loop was present or not. Resulting markers are analysed using multivariate analysis yielding specific epigenetic signatures for selected patient cohorts.
Figure 2
Figure 2
Batch adjustment by reference alignment (BARA) procedure. The scheme for batch adjustment by reference alignment (BARA) procedure [27] that was implemented in results analysis for better control of batch effects (non-biological variation).
Figure 3
Figure 3
SHapley Additive exPlanations (SHAP) values of each marker contribution in the PSE model. SHAP values (26) demonstrating the contribution of each marker in the model are shown for the binary PSA (A) and continuous PSA (B). Each dot represents one sample.
Figure 4
Figure 4
Schematic depiction of the overlap between the anchors of Episwitch loops and known PCa related SNPs on chromosome 8 from GWAS. The image shows the overlap of the anchoring sites of EpiSwitch 3D genomic markers, identified in early whole genome screening stage of EpiSwitch biomarker development [21,22], with positions of PCa SNPs from GWAS Catalogue on 8q24 chromosome region.
Figure 5
Figure 5
Schematic depiction of the genes involved in the PSE signature. The network was built using the five model markers and PSA, using the STRING DB (https://string-db.org/, accessed between 1 July and 1 October 2022). The network was generated by five additional entities that have a high confidence in interaction (data supporting the connections) suggesting high connectability at the protein level. DAPK1, HSD3B2, SRD5A3 and MMP1 model markers are circled in blue, PSA (KLK3) in red. miRNA98 is not in STRING.
See this image and copyright information in PMC

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