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August 18, 2006 –- 研究者报告支持个人化医疗的新范例之证据，使用肺恶性基因模式，分析每个病患的肿瘤的分子特征，使用这些资料进行治疗之调整；报告刊登于八月十日的新英格兰医学期刊；研究者希望遗传标记测试将可不只使用在预测病患的结果，还可以筛检最符合肿瘤分子的个人化药物。
主要作者、Durham大学的Anil Potti医师，在访谈中向Medscape强调，这是一件大事，我们从治疗一群癌症病患开始变成聚焦在有不同特征的个别病患；Potti医师表示，像肺恶性基因模式可以立即帮助医师决定哪些病患需要化疗，哪些可能风险低而可以避开化疗享有较佳的生活品质。
他的团队希望淘汰目前的肺癌肿瘤分期系统，与其将所有肿瘤小的病患都归类在早期，不如基于肿瘤的遗传标记评估他们的风险；杜克大学分子基因教授Joseph Nevins博士，同时也是本研究的资深作者，在新闻稿中做以上表示。
本研究的共同作者，杜克大学胸腔外科医师David Harpole补充，如果我们可以使用检测以增加病患存活达5%，我们每年将可以拯救10,000个生命；实际上，我认为我们还可以做得更好。
【预后工具可改变临床决策之决定】
本篇研究发表系受国家健康研究中心赞助，研究者分析89位非小细胞肺癌早期病患，他们藉评估基因表现档案预测复发风险，25位病患来自美国肿瘤医师学院研究，84位病患来自癌症与白血病B组研究。
研究者报告肺恶性基因模式预测病患复发的效果显著比临床预后因子为佳，且涵盖所有的早期非小细胞肺癌；运用于前述两个研究，他们报告指出该模式整体预测准确度为 72% 和 79%，也可鉴别有高复发风险的IA期病患，他们可能最需要化疗辅助。
使用每个肿瘤独特的遗传标记，我们的新检测方式对早期肺癌病患预测准确率高达 90%，可以预判哪些病患会有复发、哪些不会；Potti医师表示，我们现在有了工具可以将这些高风险病患从不必化疗组之中移出来到积极治疗组。
研究者目前正规划第三期临床试验，即将在六个月内开始，将包含美国和加拿大50-60个医学中心，共超过1000位病患。
Genomic Test Predicts Which Lung Cancer Patients Need Chemotherapy
By Allison Gandey
Medscape Medical News
August 18, 2006 –- Researchers report evidence of a promising new example of personalized medicine. Using a lung metagene model, the group analyzed the molecular characteristics of each patient's tumor and used that information to tailor treatment. Reporting in the August 10 issue of the New England Journal of Medicine, the researchers say they hope genomic tests like theirs will be used not only to predict patient outcomes but also to select individual drugs that will best match the tumor's molecular makeup.
"This is a huge deal," lead author Anil Potti, MD, from Duke University in Durham, North Carolina, emphasized to Medscape during an interview. "We are moving away from treating cancer patients as a population and are beginning to focus instead on single patients with individual characteristics." Dr. Potti says tests such as the lung metagene model may soon help clinicians decide which patients require chemotherapy and which may be at lower risk and can enjoy a better quality of life by avoiding that route.
His group hopes to make the current system of staging lung cancer tumors obsolete. "Instead of placing all patients with small tumors in the same early-stage category, as physicians currently would do, we can now assess their risk based on the tumor's genomic profile," Joseph Nevins, PhD, a professor of molecular genetics at Duke University and senior author of the study, says in a news release.
"If we can use the test to increase patient survival by even 5%, we would save 10,000 lives a year," David Harpole, MD, a professor of thoracic surgery at Duke and coauthor of the study, adds. "In reality, I think we can do much better than that."
Prognostic Tool Could Alter Clinical Decision-Making
In the present analysis funded by the National Institutes of Health, the researchers looked at 89 patients with early-stage non–small-cell lung cancer. They evaluated gene-expression profiles that predicted the risk of recurrence in 2 independent groups of 25 patients from the American College of Surgeons Oncology group study and 84 patients from the Cancer and Leukemia Group B study.
The investigators report that the lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of non–small-cell lung cancer. Applied to the cohorts from the 2 trials, they report that the model had an overall predictive accuracy of 72% and 79%. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy.
"Using the unique genomic signatures from each tumor, our new test predicted with up to 90% accuracy which early-stage lung cancer patients would suffer a recurrence of their cancer and which patients would not," Dr. Potti said. "We now have a tool that can be used to move these high-risk patients from the 'no-chemotherapy' group into the aggressive-treatment group."
The researchers are now recruiting for a phase 3 clinical trial. The study, to begin within 6 months, will enroll more than 1000 patients from 50 or 60 centers in the United States and Canada.
N Engl J Med. 2006; 355:570-580.