縱向代謝物資料分析於中國倉鼠卵巢細胞單株抗體生產最佳化之研究

Abstract

單株抗體(monoclonal antibody, mAb)為目前最主要也最具有價值的生物藥物 (biopharmaceutical)，而中國倉鼠卵巢細胞(Chinese hamster ovary cell)為目前生物藥物最主要的生產系統。近五十年來，細胞的抗體產量不斷的成長，主要歸功於於培養系統的改善、細胞的改良及篩選。然而，這些改良方式並非基於對生產系統(system)及機制(mechanism)的理解，而是基於經驗(empirical)，因此每一株細胞的生產條件最佳化往往需要投入大量的人力及時間才得以完成。近年來代謝體學(metabolomics)的進步，提供了進一步改善的契機。一般常用的代謝體分析方式有兩種：基於模型(model-based)以及基於統計(statistical base)的方式，兩者皆為提升抗體生產率做出不同的貢獻。然而，過去的研究鮮少提供多種定量(quantitative)的胞外(extracellular)與胞內(intracellular)代謝物(metabolites)濃度、單一細胞抗體產率、單一細胞代謝物的產出/吸收率以及細胞大小等變數間的關係，且通常只關注單一品系(cell strain)的中國倉鼠卵巢細胞於少數培養環境下的行為。因此，在此研究中，我們以超高壓液相層析儀串接紫外光譜(UHPLC-UV)以及 AbsoluteIDQ p180 Kit 兩種定量的測量分析方式，測量四種培養策略下的細胞內外代謝物濃度；並引入GASCA (Group-wise ANOVA simultaneous component analysis) 及 STATICO兩方法，分析上述變數間的多變量關係。胞外代謝物資料的主成份分析 (PCA, Principal components analysis) 結果顯示時間以及補料 (fed-batch supplement) 為影響胞外細胞代謝物輪廓 (profile) 的主要因子；而細胞特徵(cell features，包含細胞內代謝物濃度、細胞代謝物分泌速率及細胞大小等三群變數)的GASCA結果顯示，細胞特徵顯著地受到培養基(media)及時間因子和培養基、時間及細胞品系(cell strain)三因子的交互作用影響。此外，GASCA分析中Group-wise PCA所產生的主成份中所包含的變數，可以代表某些生物意義，例如細胞大小、細胞異質性 (heterogeneity)，培養過程中被過度餵食/生產的代謝物等。STATICO結果則顯示胞外代謝物濃度細胞特徵兩群變數間的關係，並指出七個可能用於改善單一細胞抗體產量的代謝物。我們選擇了白胺酸 (leucine)，異白胺酸 (isoleucine) 及組胺酸 (histidine) 三種代謝物進行驗證實驗。其結果顯示，額外添加此三種胺基酸會些微增加CHOK1細胞以Mix作為培養基Feed A/B補料的細胞的單位細胞抗體產量(cell-specific antibody production rate)，然而此增加幅度並未達到預先設定的顯著水準 (α = .10)。因此，驗證實驗的結果顯示，僅添加少量的特定的代謝物對於抗體產量的增加的效果有限，仍需要更多證據支持驗證實驗中發現的的抗體量增加並非隨機造成。

Nowadays, monoclonal antibodies (mAbs) are the most lucrative and dominance biopharmaceutical product, and Chinese hamster ovary (CHO) cells are the predominant system for their production. A constant increase in the antibody production of CHO cells during the last fifty years resulted from sustained, considerable efforts for culturing system optimization, host cell engineering, and screening. These empirical approaches are time-consuming and labor-intensive because we only have limited knowledge about the production system and the mechanism. Recently, metabolomics research sheds light on this issue. Two different approaches, including model-based methods, and statistical-based methods, are used in the cell metabolomics analysis to provide suggestions for the optimization of the production. However, previous studies only included limited metabolites, cell strains, and feeding strategies. They failed to answer which factors significantly affect the cell state: intracellular metabolite levels, cell-specific metabolite consumption rates, the size of cells, and the antibody production rate. Besides, they also failed to provide multivariate relationships between and within extracellular metabolite concentrations, and cell state. Hence, we quantitatively measured both the intra- and the extracellular metabolite concentrations of CHO cells under four culturing strategies by UHPLC-UV and AbsoluteIDQ p180 Kit. GASCA (Group-wise ANOVA simultaneous component analysis) and STATICO were introduced to extract multivariate relationships between variables. The results showed that sampling times and fed-batch supplements were the primary factors that affect the extracellular metabolite profile, and the interaction of time, cell, and media, and the main effect of media and time significantly affect the state of the cell. Besides, the loading and the score by Group-wise PCA (GPCA), the second step of GASCA, could represent biological meanings, such as cell size increment, heterogeneity of culturing cells, and possible overfed/overproduced metabolites during the culturing process. The results form STATICO showed the relationship between and within extracellular metabolite concentrations and cell state, and indicate seven metabolites that could increase the cell-specific antibody production rate. L-leucine, L-isoleucine, and L-histidine were selected to perform a validation experiment. An increment in cell-specific antibody production rate was observed; nevertheless, the increment was insignificant. The results indicated that the effect of the extra addition of a minority of extracellular metabolites for CHOK1 with Mix basal medium and FeedA/B fed-batch supplements might be limited, and more evidence is necessary to evaluate whether the increment is meaningful.