# Predicting the Diagnosis of Prostate Cancer with a Novel Blood-Based Biomarker: Comparison of Its Performance with Prostate-Specific Antigen

**Authors:** Johnmesha L. Sanders, Kenneth A. Iczkowski, Girish V. Shah

PMC · DOI: 10.3390/cancers16152619 · Cancers · 2024-07-23

## TL;DR

A new blood test using a protein called NEM is better than PSA at detecting prostate cancer and reducing false positives.

## Contribution

The study introduces NEM as a novel blood-based biomarker that outperforms PSA in prostate cancer detection.

## Key findings

- NEM had a 99% area under the ROC curve for predicting prostate cancer, compared to 81% for PSA.
- NEM showed 98% sensitivity and 97% specificity, outperforming PSA's 76% sensitivity and 95% specificity.
- NEM more accurately differentiated cancer from benign conditions like BPH or prostatitis than PSA.

## Abstract

For decades, a blood test showing elevated prostate-specific antigen (PSA) has been the mainstay for detecting prostate cancer. However, the PSA is often elevated in the absence of cancer. Here, we show that the neuroendocrine marker (NEM) outperforms the PSA test, both for sensitivity and for the exclusion of false-positive results.

The purpose of this study was to assess the efficacy, specificity, and predictive value of a newly discovered biomarker, Zinc finger-like1 protein (referred to as neuroendocrine marker, NEM) for the detection of prostate cancer (PCa). We retrospectively analyzed banked plasma samples from 508 men, with a median age of 67 years (range 48–97), to compare the performance of NEM and PSA in predicting subsequent histologic PCa. The cohort consisted of four groups of patients visiting a urology clinic: (1) patients not diagnosed with either benign prostatic disease or prostate cancer (PCa) were defined as normal; (2) patients diagnosed with benign hyperplasia (BPH) but not PCa; (3) patients with confirmed PCa; and (4) patients with cancer other than PCa. The normal men displayed a mean NEM plasma level of 0.948 ± 0.051 ng/mL, which increased to 1.813 ± 0.315 ng/mL in men with BPH, 86.49 ± 15.51 ng/mL in men with PCa, and 10.47 ± 1.029 ng/mL in men with other Ca. The corresponding concentrations of prostate-specific antigen (PSA) in these subjects were 1.787 ± 0.135, 5.405 ± 0.699, 35.77 ± 11.48 ng/mL, and 8.036 ± 0.518, respectively. Receiver operating characteristic (ROC) curve analysis was performed to compare NEM and PSA performance, and the Jouden Index for each biomarker was calculated to determine cut-off points for each biomarker. The area under the ROC curve to predict PCa was 0.99 for NEM and 0.81 for PSA (p < 0.0001). The cut-off for NEM was at 1.9 ng/mL, with sensitivity of 98% and specificity of 97%. The corresponding PSA values were 4.4 ng/mL, with sensitivity of 76% and specificity of 95%. The predictive value of each biomarker in a patient was matched with his pathologic data to determine the accuracy of each biomarker. NEM was more accurate than PSA in differentiating cancer from benign conditions, such as BPH or prostatitis. In conclusion, NEM was a better predictor of PCa than PSA in patients visiting urology clinics. NEM tests, either alone or in conjunction with other biomarkers, provide a reliable, non-invasive, and inexpensive test to remarkably reduce false positives and thereby reduce the number of diagnostic biopsies and associated painful procedures and the loss of quality of life.

## Linked entities

- **Proteins:** KLK3 (kallikrein related peptidase 3), insc (inscuteable)
- **Diseases:** prostate cancer (MONDO:0005159), BPH (MONDO:0010811), prostatitis (MONDO:0005280)

## Full-text entities

- **Genes:** KLK3 (kallikrein related peptidase 3) [NCBI Gene 354] {aka APS, KLK2A1, PSA, hK3}
- **Diseases:** benign hyperplasia (MESH:D006965), prostatitis (MESH:D011472), benign prostatic disease (MESH:D011469), cancer (MESH:D009369), PCa (MESH:D011471)
- **Chemicals:** NEM (MESH:C058866)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11311074/full.md

## References

36 references — full list in the complete paper: https://tomesphere.com/paper/PMC11311074/full.md

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Source: https://tomesphere.com/paper/PMC11311074