A blood-based multi-mRNA liquid biopsy with >90% accuracy for diagnosis and assessment of prostate cancers.

Authors

Kambiz Rahbar

Kambiz Rahbar

University Hospital Münster, Münster, Germany

Kambiz Rahbar , Mark S. Kidd , Ignat A. Drozdov , Alexandra Kitz , Anna Malczewska , Pawel Rajwa , Martin Boegemann , Christof Bernemann , Lisa Bodei , Irvin Mark Modlin

Organizations

University Hospital Münster, Münster, Germany, Wren Laboratories LLC, Branford, CT, Medical University of Silesia, Katowice, Poland, University Hospital Muenster, Münster, Germany, Department of Urology, University of Muenster, Muenster, Germany, Memorial Sloan Kettering Cancer Center, New York, NY, Yale School of Medicine, New Haven, CT

Research Funding

No funding received
None

Background: There are a paucity of blood-based biomarkers with clinical utility for prostate cancer (PCa). We developed a circulating mRNA (27-gene) prostate cancer signature to diagnose and manage PCa. Methods: Gene identification: Publicly available PCa transcriptome sets (n= 1,159 samples) were evaluated and compared with normal blood-based transcriptomes using gene co-expression network enrichment, differential expression and functional enrichment analyses to identify candidate markers. Gene expression evaluation: Seven PCA cell lines and two normal prostate epithelial lines were used to assess candidate genes. Marker genes were determined in PCa tumor tissue (n= 50) and validated in the TCGA-PRAD (n= 500) dataset. Blood gene expression: Set #I: PCA: n= 132, BPH: n= 44, controls n= 55. Set #II: n= 50 (biochemical recurrence [BCR]). We constructed an artificial intelligence PCa model using classification algorithm analyses. Scoring: normalized algorithmically analyzed gene expression (0 to 100), positive score >20. PSA: BPH (n= 44) and PCa (n= 132). Clinical score assessment: Surgical cohort: (n= 47), samples: pre-surgical and post: 1 week - 14 months. Statistics: Kruskal-Wallis, Pearson-correlation, Fisher’s and AUROC analyses (Mean±SEM). Results: Transcriptomic analysis identified 27 candidates. Cell lines/tissue: Expression levels were significantly elevated (p< 0.001, 2.1-35.8-fold) in cell lines and PCa surgical samples. All 27 markers were confirmed in TCGA-PRAD samples (average TPM: 58 to 10,366). Blood: In Set#I, levels in PCa were 47±2 (p< 0.0001) compared to BPH (19±1) and controls (18±0.5); AUROC: 0.92 (BPH) and 0.94 (controls), with an accuracy of 85-88%, a sensitivity of 86% and specificities 82 and 93%. For PSA, the AUROC (PCa vs. BPH) was 0.51 (p= 0.88). PSA was positive in 86% of BPH and was > 10ng/ml in 30%. PSA was positive in 83% of PCa and > 10ng/ml in 40% (Fisher’s p= 0.28). PSA accuracy ( > 10ng/ml) was 48%. Levels in Set#II (BCR) were 44±3. ProstaTest-was positive in 48 (96%). Surgical cohort (n= 47): Prostatest accuracy 100% pre-surgery. Resection decreased levels (KW-statistic: 57.4, p< 0.0001) from 52±1 to 23.5±2. Conclusions: A 27-gene blood signature was developed for PCa that exhibited a diagnostic accuracy of 92%; significantly better than PSA (48%, p< 0.0001). Surgical resection significantly (p< 0.0001) decreased levels. Biochemical recurrence was accurately detected (96%). A multi-gene prostate cancer liquid biopsy is likely to have clinical utility in both diagnosis and monitoring of PCa.

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Abstract Details

Meeting

2020 ASCO Virtual Scientific Program

Session Type

Poster Session

Session Title

Genitourinary Cancer—Prostate, Testicular, and Penile

Track

Genitourinary Cancer—Prostate, Testicular, and Penile

Sub Track

Prostate Cancer - Advanced Disease

Citation

J Clin Oncol 38: 2020 (suppl; abstr 5574)

DOI

10.1200/JCO.2020.38.15_suppl.5574

Abstract #

5574

Poster Bd #

155

Abstract Disclosures

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