南方医院发表权威期刊文章：首次提出癌症基于免疫评分的新模型
胃癌作为全球发病率第四位、死亡率第二位的恶性肿瘤，其治疗和预后评估一直是研究人员和临床医生十分关注的问题。基于传统TNM分期和组织学分型进行预后预测和治疗方案选择，是目前临床应用最广泛的方法。然而，尽管TNM分期和治疗方案相同，但患者预后大不相同。
在这篇文章中，研究人员利用879例胃癌患者数据，通过免疫组化分析淋巴细胞免疫特征簇和髓样细胞免疫特征簇水平，利用LASSO-COX回归模型首次建立了基于免疫特征的胃癌分类体系免疫评分（ISGC），借此预测胃癌术后复发率、无病生存率和总生存率。该研究首次提出了基于免疫评分预测胃癌患者术后生存和辅助化疗效果的模型，极大补充并完善了传统肿瘤TNM分期和组织学分型对胃癌患者预后预测和治疗的指导作用。
南方医院普通外科主任李国新表示，胃癌TNM分期作为目前临床上应用最广泛的指导患者治疗和预测预后的参考，本研究进一步说明了ISGC联合TNM分期对疾病预测的重要作用，多变量COX回归分析也表明ISGC是胃癌患者极具价值的无病生存率和总生存的独立预后因素。此外，ISGC还可用于今后指导筛选II期和III期胃癌患者能够从辅助化疗的获益人群。
2016年以来，南方医院李国新课题组已先后于Journal of Clinical Oncology(JCR 1区, IF 20.982)，Trends in pharmacological Sciences (JCR 1区, IF 11.840)，Annals of Surgery (JCR 1区, IF 8.569)，Clinical Cancer Research (JCR 2区, IF 8.738)等国际顶尖期刊发表学术成果。
作者简介：
李国新
毕业于第一军医大学，医学硕士，2006年获第一军医大学外科学及临床解剖学博士学位 。科主任，教授、主任医师，博士生导师，微创外科解剖研究所副所长。现任广东省医学会微创外科学分会常委，广东省抗癌协会大肠癌专业委员会委员、乳腺癌专业委员会委员，全军普外专业委员会乳腺、甲状腺学组委员，担任《中华实验外科》等多家杂志编委。特别擅长腹腔镜微创胃肠及甲状腺乳腺手术。创建了南方医院普外科第一个专科研究中心微创外科临床中心，是普外科微创专业的学术带头人。
原文摘要：
ImmunoScore Signature: A prognostic and predictive Tool In Gastric Cancer
OBJECTIVE: We postulated that the ImmunoScore (IS) could markedly improve the prediction of postsurgical survival and chemotherapeutic benefits in gastric cancer (GC).
SUMMARY BACKGROUND DATA: A prediction model for GC patients was developed using data from 879 consecutive patients.
METHODS: The expression of 27 immune features was detected in 251 specimens by using immunohistochemistry, and a 5-feature-based ISGC was then constructed using the LASSO Cox regression model. Testing and validation cohorts were included to validate the model.
RESULTS: Using the LASSO model, we established an ISGC classifier based on 5 features: CD3invasive margin (IM), CD3center of tumor (CT), CD8IM, CD45ROCT, and CD66bIM. Significant differences were found between the high-ISGC and low-ISGC patients in the training cohort in 5-year disease-free survival (45.0% vs. 4.4%, respectively; p <0.001) and 5-year overall survival (48.8% vs. 6.7%, respectively; p <0.001). Multivariate analysis revealed that the ISGC classifier was an independent prognostic factor. A combination of ISGC and tumor, node, and metastasis (TNM) had better prognostic value than TNM stage alone. Further analysis revealed that stage II and III GC patients with high-ISGC exhibited a favorable response to adjuvant chemotherapy. Finally, we constructed 2 nomograms to predict which patients with stages II and III GC might benefit from adjuvant chemotherapy after surgery.
CONCLUSIONS: The ISGC classifier could effectively predict recurrence and survival of GC, and complemented the prognostic value of the TNM staging system. Moreover, the ISGC might be a useful predictive tool to identify stage II and III GC patients who would benefit from adjuvant chemotherapy.
