Institute for Medical BioMathematics, Bene Ataroth, Israel.
PLoS One. 2010 Dec 8;5(12):e15482. doi: 10.1371/journal.pone.0015482.
Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.
METHODOLOGY/PRINCIPAL FINDINGS: We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2) = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.
CONCLUSIONS/SIGNIFICANCE: Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols.
针对转移性前列腺癌（PCa）的治疗性疫苗接种在某些 PCa 患者中部分有效。我们假设通过简单的数学模型定制个体化疫苗接种方案可以增强治疗效果。
方法/主要发现：我们开发了一个包含疫苗、免疫系统和 PCa 细胞基本相互作用的通用数学模型，并通过测试同种异体 PCa 全细胞疫苗的临床试验结果对其进行了验证。为了在没有任何其他相关标志物的情况下验证模型，我们使用临床上测量的前列腺特异性抗原（PSA）水平变化作为肿瘤负担的相关指标。每位患者最多可测量 26 次 PSA 水平，这些水平被分为每位患者的训练集和验证集。训练集用于模型个性化，包含患者初始 PSA 水平序列；验证集包含他随后的 PSA 数据点。个性化模型用于预测肿瘤负担和 PSA 水平的变化，并将预测结果与验证集进行比较。在 15 名接种反应性患者中的 12 名中，该模型准确地预测了整个测量期间的 PSA 水平（预测和观察到的 PSA 值之间的决定系数 R²为 0.972）。在治疗结束时，该模型无法解释 15 名反应性患者中的 3 名 PSA 水平的不一致变化。对每个经过验证的个性化模型进行了许多假设性免疫治疗方案的模拟，以提出替代疫苗接种方案。预测能增强治疗效果的个性化方案在患者之间有所不同。
结论/意义：我们使用最初的几次测量构建了稳健的 PCa 免疫治疗个体化模型，这些模型通过临床试验结果进行了回顾性验证。我们的结果强调了个体化模型建议免疫治疗方案的潜在价值和可行性。
