Evaluation of MIR-371A-3P for clinical implementation in a CLIA-certified laboratory.

M Melis Gür (Department for Urology, Urooncology, Robot-Assisted and Focal Treatment, University of Madgeburg, Magdeburg, Germany) K Kshitij Pandit (Department of Urology, University of California, San Diego Health, San Diego, CA) J John T. Lafin (Department of Urology, University of Texas Southwestern Medical Center) C Cinzia Scarpini (University of Cambridge, Cambridge, Cambridge, United Kingdom) A Armon Amini (University of Alabama at Birmingham, Birmingham, Alabama, United States) B Bendu Konneh (UT Southwestern Medical Center, Dallas, TX) J Jeffrey Howard (UT Southwestern Medical Center, Dallas, TX) T Thomas Gerald (UT Southwestern, Dallas, TX) M Michelle Nuno (3University of Southern California, Department of Population and Public Health Sciences, Los Angeles, United States) J Jin Piao (Keck School of Medicine, University of Southern California, Los Angeles, CA) N Nicholas Coleman (University of Cambridge, Cambridge, United Kingdom) L Lindsay Frazier (Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA) M Matthew Murray S Sarah Murray (University of California, San Diego, La Jolla, CA) A Aditya Bagrodia (UC San Diego Health, La Jolla, CA, 92093)

Abstract

648 Background: MicroRNAs (mi-RNAs) have emerged as promising biomarkers for the detection of viable germ cell tumors (GCT). Our previous work in a research lab demonstrated optimal performance with positive results that had Cq values less than 28, an indeterminate range between 28-35 and negative results greater than 35. In this study, we assessed performance characteristics of miR-371a-3p in a CLIA certified lab at UCSD. Methods: Due to workflows, equipment and scaling, several modifications were required from our original research protocol. Ultimately, serum samples from 53 cases and 139 controls were analyzed using qPCR for miR-371a-3p in the CLIA lab. Initial runs and re-runs were conducted for the indeterminate samples. Metrics used for calculation of performance were sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC) and Youden’s index. Results: We used two analytic pipelines for classifying positive and negative Cq values: 1) a binary cutoff of 26.9 and, 2) an indeterminate range of 25.6 to 31.5. Using the binary cutoff, a sensitivity of 86%, specificity of 98%, PPV of 94%, NPV of 95%, AUC of 0.94 and Youden index of 0.85 was observed. In contrast, initial runs on the indeterminate ranges yielded a sensitivity of 95%, specificity of 99%, PPV of 97%, NPV of 98%, AUC of 0.97 and Youden index of 0.94. However, 36% (51 of 139) controls fell into the indeterminate range. Re-runs on these samples demonstrated similar findings. Conclusions: Our data demonstrated that there are likely lab specific, protocol specific and disease-state specific analytics and thresholding for circulating miR-371a-3p testing. These factors will need to be carefully considered while moving towards clinical implementation.

Article Details

Volume / Issue Vol. 43, Issue 5_suppl
Published February 10, 2025
Pages 648-648
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (15)

M

Melis Gür

Department for Urology, Urooncology, Robot-Assisted and Focal Treatment, University of Madgeburg, Magdeburg, Germany

K

Kshitij Pandit

Department of Urology, University of California, San Diego Health, San Diego, CA

J

John T. Lafin

Department of Urology, University of Texas Southwestern Medical Center

C

Cinzia Scarpini

University of Cambridge, Cambridge, Cambridge, United Kingdom

A

Armon Amini

University of Alabama at Birmingham, Birmingham, Alabama, United States

B

Bendu Konneh

UT Southwestern Medical Center, Dallas, TX

J

Jeffrey Howard

UT Southwestern Medical Center, Dallas, TX

T

Thomas Gerald

UT Southwestern, Dallas, TX

M

Michelle Nuno

3University of Southern California, Department of Population and Public Health Sciences, Los Angeles, United States

J

Jin Piao

Keck School of Medicine, University of Southern California, Los Angeles, CA

N

Nicholas Coleman

University of Cambridge, Cambridge, United Kingdom

L

Lindsay Frazier

Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA

M

Matthew Murray

S

Sarah Murray

University of California, San Diego, La Jolla, CA

A

Aditya Bagrodia

UC San Diego Health, La Jolla, CA, 92093