Albuquerque-Castro Ângela, Macedo-Silva Catarina, Oliveira-Sousa Rúben, Constâncio Vera, Lobo João, Carneiro Isa, Henrique Rui, Jerónimo Carmen
Cancer Biology & Epigenetics Group, Research Center of IPO Porto (CI-IPOP)/ CI-IPOP@ RISE (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Center Raquel Seruca (Porto.CCC), R. Dr. António Bernardino de Almeida, 4200-072, Porto, Portugal.
Masters' in Oncology, ICBAS-School of Medicine and Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-513, Porto, Portugal.
Biomark Res. 2024 Aug 1;12(1):75. doi: 10.1186/s40364-024-00627-4.
Accurate prostate cancer (PCa) patient diagnosis and risk assessment are key to ensure the best outcome. Currently, low- and favorable intermediate-risk PCa patients may be offered AS due to the indolent nature of the disease. Nonetheless, deciding between active surveillance and curative-intent treatment remains an intricate task, as a subset of these patients may eventually progress, enduring poorer prognosis. Herein, we sought to construct risk calculators based on cancer biomarkers, enabling more accurate discrimination among patients which may benefit from active interventions.Ki67 immunoscore, GSTP1 and KLF8 promoter methylation levels () were assessed in PCa tissues. Study endpoints included overall and biochemical recurrence-free (BCR) survival. Combination with relevant clinicopathological parameters allowed for construction of graphical calculating tools (nomograms).Higher Ki67 index correlated with worse BCR-free survival, whereas higher KLF8 levels were associated with improved overall survival, especially in patients with lower-grade tumors. GSTP1 levels had no prognostic value. Among prognostic models tested, a BCR-risk calculator - ProstARK (including Ki67 and clinicopathologic parameters) - disclosed 79.17% specificity, 66.67% sensitivity, 55% positive predictive value, 86% negative predictive value, and 75.76% accuracy. Similar results were found using an independent PCa biopsy cohort, validating its prognostication ability.Combining clinicopathologic features and Ki67 index into a risk calculator enables easy and accurate implementation of a novel PCa prognostication tool. This nomogram may be useful for a more accurate selection of patients for active surveillance protocols. Nonetheless, validation in a larger, multicentric, set of diagnostic PCa biopsies is mandatory for further confirmation of these results.
准确的前列腺癌(PCa)患者诊断和风险评估是确保最佳治疗结果的关键。目前,由于疾病的惰性,低风险和有利的中风险PCa患者可能会接受主动监测(AS)。然而,在主动监测和根治性治疗之间做出决定仍然是一项复杂的任务,因为这些患者中的一部分最终可能会进展,预后较差。在此,我们试图构建基于癌症生物标志物的风险计算器,以便更准确地区分可能从积极干预中受益的患者。在PCa组织中评估了Ki67免疫评分、GSTP1和KLF8启动子甲基化水平()。研究终点包括总生存期和无生化复发(BCR)生存期。结合相关临床病理参数可构建图形计算工具(列线图)。较高的Ki67指数与较差的无BCR生存期相关,而较高的KLF8水平与改善的总生存期相关,尤其是在低级别肿瘤患者中。GSTP1水平无预后价值。在所测试的预后模型中,一种BCR风险计算器——ProstARK(包括Ki67和临床病理参数)——显示出79.17%的特异性、66.67%的敏感性、55%的阳性预测值、86%的阴性预测值和75.76%的准确性。使用独立的PCa活检队列也发现了类似结果,验证了其预后能力。将临床病理特征和Ki67指数结合到风险计算器中,能够轻松准确地应用一种新型PCa预后工具。该列线图可能有助于更准确地选择适合主动监测方案的患者。然而,需要在更大规模、多中心的一组诊断性PCa活检中进行验证,以进一步证实这些结果。