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　　為了更好的預測大腸癌患者對化療的反應，科學(xué)家利用一種新的數字模型測量不傷害健康組織前提下能夠殺死癌癥細胞所需應力量。研究結果發(fā)表在美國癌癥協(xié)會(huì )制定的《癌癥研究》雜志上，研究表明，系統醫學(xué)法在預測患者化療反應方面相比其他方法有顯著(zhù)優(yōu)勢。

　　細胞凋亡即程序性細胞死亡，是癌癥耐藥性的標志。此前的研究表明，細胞凋亡的關(guān)鍵步驟，引起線(xiàn)粒體外膜通透性的進(jìn)程由BLC-2蛋白質(zhì)家族的不同成員控制。一些家族成員促進(jìn)細胞凋亡，一些阻止細胞凋亡。此外，這些蛋白在細胞凋亡方面作用相同并且能夠相互替代，這使得預測細胞是否容易凋亡難上加難。

　　為了更好了解大腸癌化療的決策，研究者開(kāi)發(fā)了一種包含患者特征數據的集合工具。他們研究了BCL-2蛋白，確定特定蛋白質(zhì)水平并將水平錄入數字模型，計算出何種基因毒性應激水平能夠實(shí)現細胞凋亡。

　　抗結腸癌細胞培養、2期或3期結腸癌患者對于治療的應答，都是由計算出的細胞凋亡所需的應力水平來(lái)精密決定的。研究發(fā)現，個(gè)別患者BLC-2蛋白質(zhì)家族水平中異質(zhì)性程度較高，這是輔助化療成功與否的關(guān)鍵所在。

　　研究者測試了一種名為“DR/MOMP ”的臨床決策工具，并以此確定其在預測結腸癌患者對治療的反應效果。利用DR/MOMP 能準確預測患者預后。

　　這一發(fā)現可能提供一種臨床決策的工具，能夠預測結腸癌患者的治療效果。研究提供細胞凋亡的定量動(dòng)態(tài)分析，并能夠為個(gè)體患者預測治療效果。

　　New model may help predict response to chemotherapy for colorectal cancer

　　PHILADELPHIA — Scientists may be able to better predict which patients with colorectal cancer will respond to chemotherapy using a new mathematical model that measures the amount of stress required for a cancer cell to die without harming healthy tissue. The results of this study are published in Cancer Research, a journal of the American Association for Cancer Research.

　　"Our study demonstrates that systems medicine approaches (i.e., quantitative analysis of multiple factors in patients' samples combined with mathematical modeling) have a significant advantage over other approaches in predicting therapy responses in patients," said Jochen J.M. Prehn, Ph.D., director of the Centre for Systems Medicine at the Royal College of Surgeons in Ireland.

　　Apoptosis, or programmed cell death, is believed to be a hallmark of cancer resistance to chemotherapy. Prior research has shown that the key step in apoptosis, the process that leads to mitochondrial outer membrane permeabilization (MOMP) is controlled by different members of the BCL-2 family of proteins. Some family members promote apoptosis and some prevent it. In addition, those proteins that have the same effects on apoptosis work in parallel and can substitute for each other, which makes it difficult to predict whether cells are likely or unlikely to die.

　　To better inform decision-making in chemotherapy for colorectal cancer, Prehn and colleagues developed a tool that would incorporate patient-specific, molecular data sets. They studied the BCL-2 proteins, determined levels of the individual proteins and put the levels into a mathematical model that calculated what genotoxic stress level is needed to achieve apoptosis.

　　"Resistance of colon cancer cells in culture, as well as treatment responses of patients with stages 2 and 3 colon cancer, were critically determined by the calculated stress level required to undergo apoptosis," Prehn said. "We found that individual patients had a high degree of heterogeneity in BCL-2 family protein levels and that this was a potential cause of the success or failure of adjuvant chemotherapy."

　　Prehn and colleagues tested a clinical decision-making tool that they call DR_MOMP to determine its use in predicting treatment responses in patients with colon cancer. Using DR_MOMP, they were able to robustly predict patient outcome.

　　"This finding may provide a clinical decision-making tool that enables predictions of treatment responses in patients with colon cancer," Prehn said. "As we provide a quantitative, dynamic analysis of the process of apoptosis, we can also calculate, for individual patients, the therapeutic window."

　　The model could help predict how much genotoxic stress is required for a cancer cell to die before normal tissue is affected. Prehn and colleagues hope to validate DR_MOMP in other cancers and in larger patient cohorts.

　　"We need to develop easy and accessible protein profiling and modeling platforms that enable the implementation of this new technology in clinical trials and in pathology laboratories," Prehn said.