Fazzari Jennifer, Sidhu Jesse, Motkur Shreya, Inman Mark, Buckley Norman, Clemons Mark, Vandermeer Lisa, Singh Gurmit
Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada.
Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
J Pain Res. 2020 Feb 7;13:313-321. doi: 10.2147/JPR.S227175. eCollection 2020.
Cancers originating in the breast, lung and prostate often metastasize to the bone, frequently resulting in cancer-induced bone pain that can be challenging to manage despite conventional analgesic therapy. This exploratory study's aim was to identify potential biomarkers associated with cancer-induced pain by examining a sample population of breast cancer patients undergoing bisphosphonate therapy.
A secondary analysis of the primary study was performed to quantify serum cytokine levels for correlation to pain scores. Cytokines with statistically significant correlations were then input into a stepwise regression analysis to generate a predictive equation for a patient's pain severity. In an effort to find additional potential biomarkers, correlation analysis was performed between these factors and a more comprehensive panel of cytokines and chemokines from breast, lung, and prostate cancer patients.
Statistical analysis identified nine cytokines (GM-CSF, IFNγ, IL-1β, IL-2, IL-4, IL-5, IL-12p70, IL-17A, and IL-23) that had significant negative correlations with pain scores and they could best predict pain severity through a predictive equation generated for this specific evaluation. After performing a correlation analysis between these factors and a larger panel of cytokines and chemokines, samples from breast, lung and prostate patients showed distinct correlation profiles, highlighting the clinical challenge of applying pain-associated cytokines related to more defined nociceptive states, such as arthritis, to a cancer pain state.
Exploratory analyses such as the ones presented here will be a beneficial tool to expand insights into potential cancer-specific nociceptive mechanisms and to develop novel therapeutics.
起源于乳腺、肺和前列腺的癌症常转移至骨骼，频繁导致癌症诱发的骨痛，尽管采用传统镇痛疗法，这种疼痛仍难以控制。本探索性研究的目的是通过检查接受双膦酸盐治疗的乳腺癌患者样本群体，确定与癌症诱发疼痛相关的潜在生物标志物。
对原研究进行二次分析，以量化血清细胞因子水平与疼痛评分的相关性。然后将具有统计学显著相关性的细胞因子纳入逐步回归分析，以生成患者疼痛严重程度的预测方程。为了寻找更多潜在的生物标志物，对这些因素与来自乳腺癌、肺癌和前列腺癌患者的更全面的细胞因子和趋化因子组进行了相关性分析。
统计分析确定了九种细胞因子（粒细胞-巨噬细胞集落刺激因子、干扰素γ、白细胞介素-1β、白细胞介素-2、白细胞介素-4、白细胞介素-5、白细胞介素-12p70、白细胞介素-17A和白细胞介素-23）与疼痛评分呈显著负相关，并且它们可以通过为此特定评估生成的预测方程最好地预测疼痛严重程度。在对这些因素与更大的细胞因子和趋化因子组进行相关性分析后，乳腺癌、肺癌和前列腺癌患者的样本显示出不同的相关性特征，突出了将与更明确的伤害性状态（如关节炎）相关的疼痛相关细胞因子应用于癌症疼痛状态的临床挑战。
本文所呈现的此类探索性分析将成为一种有益的工具，有助于拓展对潜在癌症特异性伤害性机制的认识，并开发新的治疗方法。
