Rapid Diagnosis of Prostate Cancer Disease Progression Using Paper Spray Ionization Mass Spectrometry

The
limitation of prostate specific antigen (PSA) for prostate
cancer (PC) diagnosis is well-recognized. The Gleason score (GS) has
been the most widely used grading system for prostate tumor differentiation
and represents the best-established prognostic indicator for prostate
cancer progression. However, a rapid and sensitive noninvasive diagnostic
marker that differentiates GS-based prostate cancer disease progression
is needed. As PC is becoming a leading cause of cancer related death
for men in the U.S. and worldwide, an immediate need exists for an
improved, sensitive, noninvasive, and rapid diagnostic test for PC
screening. Here, we employed paper spray ionization-mass spectrometry
(PSI MS)-based global metabolomics of urine liquid biopsies to distinguish
between healthy (negative for any prostate specific health problems)
and progressive PC states (low grade PC such as GS6 and high-grade
PC such as GS7, GS8, and GS9). For PSI-MS-based direct untargeted
metabolic investigation, a raw urine sample was directly pipetted
onto a triangular paper substrate, without any additional sample preparation.
Multivariate statistical analysis revealed distinct GS-specific metabolic
signatures compared to a healthy control. Variable importance in projection
from partial least-squares-discriminant analysis showed distinct metabolic
patterns that were correlatively elevated with progressive disease
and could serve as biomarkers for diagnosis of prostate cancer risk
categorization.

前列腺特异性抗原（prostate specific antigen, PSA）用于前列腺癌（prostate cancer, PC）诊断的局限性已得到广泛公认。格里森评分（Gleason score, GS）作为目前应用最广泛的前列腺肿瘤分化分级系统，是前列腺癌进展领域最成熟的预后指标。然而，当前仍亟需一种快速、灵敏的非侵入性诊断标志物，以区分基于格里森评分的前列腺癌疾病进展状态。鉴于前列腺癌已成为美国乃至全球男性癌症相关死亡的首要病因，开发更灵敏、非侵入且快速的前列腺癌筛查诊断手段已迫在眉睫。本研究采用基于纸喷雾电离质谱（paper spray ionization-mass spectrometry, PSI MS）的尿液液体活检全局代谢组学方法，对健康个体（无任何前列腺相关健康问题）与进展性前列腺癌患者（包括格里森评分6级的低级别前列腺癌，以及格里森评分7、8、9级的高级别前列腺癌）进行区分。在基于PSI-MS的直接非靶向代谢研究中，未经过任何额外样品前处理的原始尿液样本可直接移取至三角纸质基底上。多元统计分析结果显示，与健康对照组相比，前列腺癌患者存在显著的格里森评分特异性代谢特征谱。通过偏最小二乘判别分析（partial least-squares-discriminant analysis）得到的投影变量重要性分析表明，存在与疾病进展呈相关性升高的独特代谢模式，此类代谢物可作为前列腺癌风险分层诊断的生物标志物。