br Clinical Genitourinary Cancer Vol No Elsevier Inc All rig
Clinical Genitourinary Cancer, Vol. 17, No. 3, 183-90 ª 2019 Elsevier Inc. All rights reserved. Keywords: Gas chromatography-mass spectrometry, Metabolomics, Nonparametric statistics, Prostatic neoplasms, Stir bar sorptive extraction
1Department of Chemistry and Biochemistry
2Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 3The Clinic Internal Medicine, El Paso, TX 4Geisinger Medical Center, Danville, PA
Addresses for correspondence: Wen-Yee Lee, PhD, Department of Chemistry and Biochemistry, University of Texas at El Paso, 500 W University Ave, El Paso, TX 79968; Heinric Williams, MD, Department of Urology, Geisinger Clinic, M.C. 13-16, 100 North Academy Avenue, Danville, PA 17822 E-mail contact: [email protected]; [email protected]
In the United States, prostate cancer (PCa) is the most common non-cutaneous cancer and the second leading cause of cancer death in men.1 Serum prostate-specific antigen (PSA) is the most commonly used biomarker for PCa. However, PSA lacks accuracy for PCa diagnosis and, as a result, contributes to unnecessary prostate biopsies, overdiagnosis, and overtreatment of the disease.2 Therefore, finding more sensitive and reliable PCa screening methods is greatly needed.
In the United States, approximately 19 million men undergo serum PSA blood testing annually,3 resulting in 4.7 million
Urinary VOCs for Prostate Cancer Diagnosis
abnormal PSA test results ( 4.0 ng/mL), and leading to 1.3 million biopsy procedures.4 Only 22% of men undergoing their first biopsy will be diagnosed with PCa.5 In addition, more than one-third of the men with PCa on prostate biopsy will have clinically indolent or low-risk disease. Thus, a better screening assay that detects clinically significant PCa could potentially eliminate nearly 80% (w1 million) of prostate biopsies, avoiding the unnecessary expense and the associated risks of pain, infection, bleeding, difficulty uri-nating, and anxiety.6 Therefore, developing an effective diagnostic test capable of not only identifying men with PCa, but more importantly, those with clinically significant disease, is needed.
Metabolic reprogramming is a well-recognized hallmark of can-cer, and metabolomic approaches have shown promise in oncology diagnosis, prognostic, and treatment.7 Studies reported that trained animals can detect cancers by “sniffing” the Corn oil from patients with breast,8 bladder,9 prostate,10,11 colorectal,12 and lung cancer.13 In PCa studies, trained dogs were able to discriminate between patients with and without disease (sensitivity and specificity > 90%).10 Because the odor of urine perceived by the dogs is produced by volatile organic compounds (VOCs), gas chromatography-mass spectrometry (GC/MS) has been proposed to detect VOCs in men for PCa.
In general, VOCs can be produced from the human body and released through breath, blood, skin, urine, and feces.14 As these VOCs are thought to reflect the physiological and metabolic status of the individual,15 they could represent tumor biology and response to therapy in individuals with cancer.15 In addition, VOCs can be conveniently and reliably detected by GC-MS, or gas sen-sors,16,17 which highlights the easy translatability of this application if successful. Taken together, the results of the previous studies coupled with the versality of VOC detection using GC-MS provided the framework to systematically study urinary VOCs as potentially biomarkers for PCa diagnosis. The model was developed and evaluated with the aid of statistical machine learning tech-niques, and its performance was compared with the current standard (ie, the PSA test).
to rule out infection prior to office-based transrectal ultrasound-guided prostate biopsy by a single provider (HW). The remaining urine samples (50 mL) were collected and stored at 80 C prior to VOC analysis. Patients with a positive PCa diagnosis represented the cancer cases. Those with benign prostate or low-volume ( 2 of 13 cores involved) high-grade prostate intraepithelial neoplasia or atyp-ical small acinar proliferation were included in the control group so as to mimic the real world clinical scenario. The 2 patients with low-volume atypical small acinar proliferation had a negative repeat 6-month prostate biopsy. The study consisted of 2 cohorts: training and testing. In the training cohort, 108 men (age, 40-84 years) were included (Table 1). Of the 108 men, 55 were diagnosed with PCa, whereas 53 were negative for PCa (herein, called controls). To validate the developed PCa diagnostic model, urine specimens from 53 PCa-positive and 22 PCa-negative patients (herein, called the testing cohort) were obtained from an internist (MHA) with the Clinic In-ternal Medicine of El Paso, TX. Specimens were obtained prior to patient referral to urology. Patients were subdivided into their respective groups based on prostate biopsy results as described for the training group.