Grenville Zoe S, Noor Urwah, Rinaldi Sabina, Gunter Marc J, Ferrari Pietro, Agnoli Claudia, Amiano Pilar, Catalano Alberto, Chirlaque María Dolores, Christakoudi Sofia, Guevara Marcela, Johansson Matthias, Kaaks Rudolf, Katzke Verena, Masala Giovanna, Olsen Anja, Papier Keren, Sánchez Maria-Jose, Schulze Matthias B, Tjønneland Anne, Tong Tammy Y N, Tumino Rosario, Weiderpass Elisabete, Zamora-Ros Raul, Key Timothy J, Smith-Byrne Karl, Schmidt Julie A, Travis Ruth C
Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Int J Cancer. 2025 Mar 1;156(5):943-952. doi: 10.1002/ijc.35208. Epub 2024 Oct 8.
Measuring pre-diagnostic blood metabolites may help identify novel risk factors for prostate cancer. Using data from 4387 matched case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we investigated the associations of 148 individual metabolites and three previously defined metabolite patterns with prostate cancer risk. Metabolites were measured by liquid chromatography-mass spectrometry. Multivariable-adjusted conditional logistic regression was used to estimate the odds ratio per standard deviation increase in log metabolite concentration and metabolite patterns (OR1SD) for prostate cancer overall, and for advanced, high-grade, aggressive. We corrected for multiple testing using the Benjamini-Hochberg method. Overall, there were no associations between specific metabolites or metabolite patterns and overall, aggressive, or high-grade prostate cancer that passed the multiple testing threshold (padj <0.05). Six phosphatidylcholines (PCs) were inversely associated with advanced prostate cancer diagnosed at or within 10 years of blood collection. metabolite patterns 1 (64 PCs and three hydroxysphingomyelins) and 2 (two acylcarnitines, glutamate, ornithine, and taurine) were also inversely associated with advanced prostate cancer; when stratified by follow-up time, these associations were observed for diagnoses at or within 10 years of recruitment (OR 0.80, 95% CI 0.66-0.96 and 0.76, 0.59-0.97, respectively) but were weaker after longer follow-up (0.95, 0.82-1.10 and 0.85, 0.67-1.06). Pattern 3 (8 lyso PCs) was associated with prostate cancer death (0.82, 0.68-0.98). Our results suggest that the plasma metabolite profile changes in response to the presence of prostate cancer up to a decade before detection of advanced-stage disease.
测量诊断前血液代谢物可能有助于识别前列腺癌的新风险因素。利用欧洲癌症与营养前瞻性调查（EPIC）研究中4387对匹配的病例对照的数据，我们研究了148种个体代谢物和三种先前定义的代谢物模式与前列腺癌风险的关联。代谢物通过液相色谱 - 质谱法测量。多变量调整的条件逻辑回归用于估计前列腺癌总体以及晚期、高级别、侵袭性前列腺癌的对数代谢物浓度和代谢物模式每增加一个标准差的比值比（OR1SD）。我们使用Benjamini-Hochberg方法校正多重检验。总体而言，特定代谢物或代谢物模式与总体、侵袭性或高级别前列腺癌之间不存在通过多重检验阈值（padj <0.05）的关联。六种磷脂酰胆碱（PCs）与采血时或采血后10年内诊断的晚期前列腺癌呈负相关。代谢物模式1（64种PCs和三种羟基鞘磷脂）和2（两种酰基肉碱、谷氨酸、鸟氨酸和牛磺酸）也与晚期前列腺癌呈负相关；按随访时间分层时，这些关联在招募时或招募后10年内的诊断中观察到（分别为OR 0.80，95% CI 0.66 - 0.96和0.76，0.59 - 0.97），但随访时间较长后关联较弱（0.95，0.82 - 1.10和0.85，0.67 - 1.06）。模式3（8种溶血PCs）与前列腺癌死亡相关（0.82，0.68 - 0.98）。我们的结果表明，在晚期疾病检测前长达十年的时间里，血浆代谢物谱会因前列腺癌的存在而发生变化。
